Automatic facial expression analysis is an area of great research especially in the field of computer vision and robotics. In the work done so far, the facial expression analysis is done either by recognizing the facial expression directly or indirectly by first recognizing AUs and then applying this information for facial expression analysis. The various challenges in facial expression analysis are associated with face detection and tracking, facial feature extraction and the facial feature classification. The presented review gives a brief description of the time line view of the research work carried for AU detection/estimation in static and dynamic image sequences and possible solutions proposed by researchers in this field since 2002. In short, the paper will provide an impetus for various challenges and applications of AU detection, and new research topics, which will increase the productivity in this exciting and challenging field.
Emotion Recognition from Facial Expression Based on Fiducial Points Detection...IJECEIAES
The importance of emotion recognition lies in the role that emotions play in our everyday lives. Emotions have a strong relationship with our behavior. Thence, automatic emotion recognition, is to equip the machine of this human ability to analyze, and to understand the human emotional state, in order to anticipate his intentions from facial expression. In this paper, a new approach is proposed to enhance accuracy of emotion recognition from facial expression, which is based on input features deducted only from fiducial points. The proposed approach consists firstly on extracting 1176 dynamic features from image sequences that represent the proportions of euclidean distances between facial fiducial points in the first frame, and faicial fiducial points in the last frame. Secondly, a feature selection method is used to select only the most relevant features from them. Finally, the selected features are presented to a Neural Network (NN) classifier to classify facial expression input into emotion. The proposed approach has achieved an emotion recognition accuracy of 99% on the CK+ database, 84.7% on the Oulu-CASIA VIS database, and 93.8% on the JAFFE database.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Multi Local Feature Selection Using Genetic Algorithm For Face IdentificationCSCJournals
Face recognition is a biometric authentication method that has become more significant and relevant in recent years. It is becoming a more mature technology that has been employed in many large scale systems such as Visa Information System, surveillance access control and multimedia search engine. Generally, there are three categories of approaches for recognition, namely global facial feature, local facial feature and hybrid feature. Although the global facial-based feature approach is the most researched area, this approach is still plagued with many difficulties and drawbacks due to factors such as face orientation, illumination, and the presence of foreign objects. This paper presents an improved offline face recognition algorithm based on a multi-local feature selection approach for grayscale images. The approach taken in this work consists of five stages, namely face detection, facial feature (eyes, nose and mouth) extraction, moment generation, facial feature classification and face identification. Subsequently, these stages were applied to 3065 images from three distinct facial databases, namely ORL, Yale and AR. The experimental results obtained have shown that recognition rates of more than 89% have been achieved as compared to other global-based features and local facial-based feature approaches. The results also revealed that the technique is robust and invariant to translation, orientation, and scaling.
Fuzzy logic is an interesting theory that allows the natural description, in linguistic terms, of problems that should be solved rather than in terms of relationships between precise numerical values. In this paper, an effective approach is proposed that quantifies the human facial expression using Mamdani implication based fuzzy logic system. The new technique involves in extracting mathematical data from
the face and fed to a fuzzy rule-based system. Fuzzification and Defuzzification operation issues trapezoidal membership functions for both input and output. The distinct feature of a system is its simplicity and high accuracy. Experimental results on Image dataset indicate good performance of the
proposed technique. Comparative analysis reveal that the proposed technique is uniqueness and robust
with reference to other state of the art methods.
In this paper, a legitimate procedure proposed for quantification of human facial expression recognition from Facial features using Mamdani-type fuzzy system. It is Fuzzy Inference System (FIS), which is capable to set up an easy membership relation between the different dimensions of the happy expression. The FIS recognizes three levels of same happy expression namely No happy, Bit Smiley and Loud Laugh based on membership function modeled on different psychological studies and surveys.
Emotion Recognition from Facial Expression Based on Fiducial Points Detection...IJECEIAES
The importance of emotion recognition lies in the role that emotions play in our everyday lives. Emotions have a strong relationship with our behavior. Thence, automatic emotion recognition, is to equip the machine of this human ability to analyze, and to understand the human emotional state, in order to anticipate his intentions from facial expression. In this paper, a new approach is proposed to enhance accuracy of emotion recognition from facial expression, which is based on input features deducted only from fiducial points. The proposed approach consists firstly on extracting 1176 dynamic features from image sequences that represent the proportions of euclidean distances between facial fiducial points in the first frame, and faicial fiducial points in the last frame. Secondly, a feature selection method is used to select only the most relevant features from them. Finally, the selected features are presented to a Neural Network (NN) classifier to classify facial expression input into emotion. The proposed approach has achieved an emotion recognition accuracy of 99% on the CK+ database, 84.7% on the Oulu-CASIA VIS database, and 93.8% on the JAFFE database.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Multi Local Feature Selection Using Genetic Algorithm For Face IdentificationCSCJournals
Face recognition is a biometric authentication method that has become more significant and relevant in recent years. It is becoming a more mature technology that has been employed in many large scale systems such as Visa Information System, surveillance access control and multimedia search engine. Generally, there are three categories of approaches for recognition, namely global facial feature, local facial feature and hybrid feature. Although the global facial-based feature approach is the most researched area, this approach is still plagued with many difficulties and drawbacks due to factors such as face orientation, illumination, and the presence of foreign objects. This paper presents an improved offline face recognition algorithm based on a multi-local feature selection approach for grayscale images. The approach taken in this work consists of five stages, namely face detection, facial feature (eyes, nose and mouth) extraction, moment generation, facial feature classification and face identification. Subsequently, these stages were applied to 3065 images from three distinct facial databases, namely ORL, Yale and AR. The experimental results obtained have shown that recognition rates of more than 89% have been achieved as compared to other global-based features and local facial-based feature approaches. The results also revealed that the technique is robust and invariant to translation, orientation, and scaling.
Fuzzy logic is an interesting theory that allows the natural description, in linguistic terms, of problems that should be solved rather than in terms of relationships between precise numerical values. In this paper, an effective approach is proposed that quantifies the human facial expression using Mamdani implication based fuzzy logic system. The new technique involves in extracting mathematical data from
the face and fed to a fuzzy rule-based system. Fuzzification and Defuzzification operation issues trapezoidal membership functions for both input and output. The distinct feature of a system is its simplicity and high accuracy. Experimental results on Image dataset indicate good performance of the
proposed technique. Comparative analysis reveal that the proposed technique is uniqueness and robust
with reference to other state of the art methods.
In this paper, a legitimate procedure proposed for quantification of human facial expression recognition from Facial features using Mamdani-type fuzzy system. It is Fuzzy Inference System (FIS), which is capable to set up an easy membership relation between the different dimensions of the happy expression. The FIS recognizes three levels of same happy expression namely No happy, Bit Smiley and Loud Laugh based on membership function modeled on different psychological studies and surveys.
A Comprehensive Survey on Human Facial Expression DetectionCSCJournals
In the recent years recognition of Human's Facial Expression has been very active research area in computer vision. There have been several advances in the past few years in terms of face detection and tracking, feature extraction mechanisms and the techniques used for expression classification. This paper surveys some of the published work since 2001. The paper gives a time-line view of the advances made in this field, the applications of automatic face expression recognizers, the characteristics of an ideal system, the databases that have been used and the advances made in terms of their standardization and a detailed summary of the state of the art. The paper also discusses facial parameterization using FACS Action Units (AUs) and advances in face detection, tracking and feature extraction methods. It has the important role in the humancomputer interaction (HCI) systems. There are multiple methods devised for facial feature extraction which helps in identifying face and facial expressions.
An eye tracker analysis of the influence of applicant attractiveness on emplo...Hakan Boz
Abstract: Tourism sector is one of the biggest service sectors in the world economy. Not just because of its number of staffs but also due to sector income. The importance of this sector in Turkey increases day by day as well. One of the Structural problems of this sector, which provides almost %5 of the GDP of Turkey, is that labor turnover rate is relatively high. This ratio increases up to %300 according to claims of several studies, and this causes great loss of productivity and income for the tourism companies. Due to the continuous change of employees, companies have difficulty in reaching standard of service and as a result of this difficulty, the possibility of appearance of service errors increases. The problems related to the inexperience staff decrease the customer satisfaction and also they have negative effects on companies’ image.
This study aims to explore the role and influence of attractiveness/attractively on the recruitment process in the touristourism and hospitality sector. The study particularly aims to measure the influence of attractiveness on the selection of job candidates by human resource managers or other managers involved in recruitment. Particularly, the study aims explore to what extent managers act rationally or under the influence of Pavlovian conditioning in making their recruitment decisions. That is to what extent managers resort to heuristics, i.e. make their decision based on the attractively of the candidate, though her/his attractively should not matter as the two positions are back stage positions.
In this study, a part of neurologic data gathering techniques of Eye Tracker(ET) will be used, thereby it is planned to obtain results concerning how much the factor of attractiveness is important in evaluating the candidates who applied a position in tourism sector.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Happiness Expression Recognition at Different Age ConditionsEditor IJMTER
Recognition of different internal emotions of human face under various critical
conditions is a difficult task. Facial expression recognition with different age variations is
considered in this study. This paper emphasizes on recognition of facial expression like
happiness mood of nine persons using subspace methods. This paper mainly focuses on new
robust subspace method which is based on Proposed Euclidean Distance Score Level Fusion
(PEDSLF) using PCA, ICA, SVD methods. All these methods and new robust method is
tested with FGNET database. An automatic recognition of facial expressions is being carried
out. Comparative analysis results surpluses PEDSLF method is more accurate for happiness
emotional facial expression recognition.
An Efficient Face Recognition Using Multi-Kernel Based Scale Invariant Featur...CSCJournals
Face recognition has gained significant attention in research community due to its wide range of commercial and law enforcement applications. Due to the developments in the past few decades, in the current scenario, face recognition is employing advanced feature identification techniques and matching methods. In spite of vast research done, face recognition still remains an open problem due to the challenges posed by illumination, occlusions, pose variation, scaling, etc. This paper is aimed at proposing a face recognition technique with high accuracy. It focuses on face recognition based on improved SIFT algorithm. In the proposed approach, the face features are extracted using a novel multi-kernel function (MKF) based SIFT technique. The classification is done using SVM classifier. Experimental results shows the superiority of the proposed algorithm over the SIFT technique. Evaluation of the proposed approach is done on CVL face database and experimental results shows that the proposed approach has a recognition rate of 99%.
Now days, the task of face recognition is widely used application of image analysis as well as pattern recognition. In biometric area of the research, automatically face & face expression recognition attracts researcher’s interest. For classifying facial expressions into different categories, it is necessary to extract important facial features which contribute in identifying proper and particular expressions. Recognition and classification of human facial expression by computer is an important issue to develop automatic facial expression recognition system in vision community. In this paper the facial expression recognition system is proposed.
ENHANCING THE HUMAN EMOTION RECOGNITION WITH FEATURE EXTRACTION TECHNIQUESIAEME Publication
Human emotions are states of mental health that resolve spontaneously rather than through conscious exertion, and are accompanied by physiological changes in the facial muscles that signify expressions. Nonverbal communication methods such as expressions, eye movements, and gestures are used in many applications of human computer interaction. Identifying emotions is not an easy task because there is no difference between the emotions of a face, and there is also a lot of complexity and variability. The machine learning algorithm uses some open features to model the face. Automatic emotion recognition based on facial expression is an interesting research field, which has presented and applied in several areas such as safety, health and in human machine interfaces. Researches in this field are interested in developing techniques to interpret, code facial expressions and extract these features in order to have a better prediction by computer. Machine learning, one of the top emerging sciences, has an extensive range of applications. In this paper, the optimization techniques-based feature extraction techniques are used to enhance the recognition of the human emotion using facial images. The optimization techniques like Ant Colony Optimization, Particle Swarm Optimization, Genetic Algorithm are used. Various metrics are used to evaluate the performance of the feature extraction techniques for emotion recognition.
Combining left and right palmprint images for more accurate personal identifi...Shakas Technologies
Multibiometrics can provide higher identificationaccuracy than single biometrics, so it is more suitable forsome real-world personal identification applications that needhigh-standard security. Among various biometrics technologies,palmprint identification has received much attention because ofits good performance.
Combining left and right palmprint images for more accurate personal identifi...LogicMindtech Nologies
IMAGE PROCESSING Projects for M. Tech, IMAGE PROCESSING Projects in Vijayanagar, IMAGE PROCESSING Projects in Bangalore, M. Tech Projects in Vijayanagar, M. Tech Projects in Bangalore, IMAGE PROCESSING IEEE projects in Bangalore, IEEE 2015 IMAGE PROCESSING Projects, MATLAB Image Processing Projects, MATLAB Image Processing Projects in Bangalore, MATLAB Image Processing Projects in Vijayangar
Biometrics was developed with the aim of improving the overall security level in all society contexts. A biometric system describes a set of techniques to analyze certain individual's biometric features, store and then using those patterns to identify or verify the identity of a person. The palmprint contains not only principal curves and wrinkles but also rich texture and miniscule points, so the palmprint identification is able to achieve a high accuracy because of available rich information in palmprint. Various palmprint identification methods, such as coding based methods and principal curve methods have been proposed in past decades. In addition to these methods, subspace based methods can also perform well for palmprint identification. Combining the left and right palmprint images to perform multibiometrics is easy to implement and can obtain better results.
Multimodal biometrics can provide higher identification accuracy than single or unimodal biometrics, so it is more suitable for some real-world personal identification applications that need high-standard security. A onetime password is included for higher security and accuracy.
One time passwords generally expire after using once. They are generated for using it within a certain time period after which it is useless. These passwords are set as a secondary security measure for the primary palmprint recognition.
Combining left and right palmprint images forjpstudcorner
To get this project in ONLINE or through TRAINING Sessions,
Contact:JP INFOTECH, Old No.31, New No.86, 1st Floor, 1st Avenue, Ashok Pillar, Chennai -83. Landmark: Next to Kotak Mahendra Bank. Pondicherry Office: JP INFOTECH, #45, Kamaraj Salai, Thattanchavady, Puducherry -9. Landmark: Next to VVP Nagar Arch. Mobile: (0) 9952649690 , Email: jpinfotechprojects@gmail.com, web: www.jpinfotech.org Blog: www.jpinfotech.blogspot.com
Fiducial Point Location Algorithm for Automatic Facial Expression Recognitionijtsrd
We present an algorithm for the automatic recognition of facial features for color images of either frontal or rotated human faces. The algorithm first identifies the sub images containing each feature, afterwards, it processes them separately to extract the characteristic fiducial points. Then Calculate the Euclidean distances between the center of gravity coordinate and the annotated fiducial points coordinates of the face image. A system that performs these operations accurately and in real time would form a big step in achieving a human like interaction between man and machine. This paper surveys the past work in solving these problems. The features are looked for in down sampled images, the fiducial points are identified in the high resolution ones. Experiments indicate that our proposed method can obtain good classification accuracy. D. Malathi | A. Mathangopi | Dr. D. Rajinigirinath ""Fiducial Point Location Algorithm for Automatic Facial Expression Recognition"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd21754.pdf
Paper URL: https://www.ijtsrd.com/computer-science/data-miining/21754/fiducial-point-location-algorithm-for-automatic-facial-expression-recognition/d-malathi
A Comprehensive Survey on Human Facial Expression DetectionCSCJournals
In the recent years recognition of Human's Facial Expression has been very active research area in computer vision. There have been several advances in the past few years in terms of face detection and tracking, feature extraction mechanisms and the techniques used for expression classification. This paper surveys some of the published work since 2001. The paper gives a time-line view of the advances made in this field, the applications of automatic face expression recognizers, the characteristics of an ideal system, the databases that have been used and the advances made in terms of their standardization and a detailed summary of the state of the art. The paper also discusses facial parameterization using FACS Action Units (AUs) and advances in face detection, tracking and feature extraction methods. It has the important role in the humancomputer interaction (HCI) systems. There are multiple methods devised for facial feature extraction which helps in identifying face and facial expressions.
An eye tracker analysis of the influence of applicant attractiveness on emplo...Hakan Boz
Abstract: Tourism sector is one of the biggest service sectors in the world economy. Not just because of its number of staffs but also due to sector income. The importance of this sector in Turkey increases day by day as well. One of the Structural problems of this sector, which provides almost %5 of the GDP of Turkey, is that labor turnover rate is relatively high. This ratio increases up to %300 according to claims of several studies, and this causes great loss of productivity and income for the tourism companies. Due to the continuous change of employees, companies have difficulty in reaching standard of service and as a result of this difficulty, the possibility of appearance of service errors increases. The problems related to the inexperience staff decrease the customer satisfaction and also they have negative effects on companies’ image.
This study aims to explore the role and influence of attractiveness/attractively on the recruitment process in the touristourism and hospitality sector. The study particularly aims to measure the influence of attractiveness on the selection of job candidates by human resource managers or other managers involved in recruitment. Particularly, the study aims explore to what extent managers act rationally or under the influence of Pavlovian conditioning in making their recruitment decisions. That is to what extent managers resort to heuristics, i.e. make their decision based on the attractively of the candidate, though her/his attractively should not matter as the two positions are back stage positions.
In this study, a part of neurologic data gathering techniques of Eye Tracker(ET) will be used, thereby it is planned to obtain results concerning how much the factor of attractiveness is important in evaluating the candidates who applied a position in tourism sector.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Happiness Expression Recognition at Different Age ConditionsEditor IJMTER
Recognition of different internal emotions of human face under various critical
conditions is a difficult task. Facial expression recognition with different age variations is
considered in this study. This paper emphasizes on recognition of facial expression like
happiness mood of nine persons using subspace methods. This paper mainly focuses on new
robust subspace method which is based on Proposed Euclidean Distance Score Level Fusion
(PEDSLF) using PCA, ICA, SVD methods. All these methods and new robust method is
tested with FGNET database. An automatic recognition of facial expressions is being carried
out. Comparative analysis results surpluses PEDSLF method is more accurate for happiness
emotional facial expression recognition.
An Efficient Face Recognition Using Multi-Kernel Based Scale Invariant Featur...CSCJournals
Face recognition has gained significant attention in research community due to its wide range of commercial and law enforcement applications. Due to the developments in the past few decades, in the current scenario, face recognition is employing advanced feature identification techniques and matching methods. In spite of vast research done, face recognition still remains an open problem due to the challenges posed by illumination, occlusions, pose variation, scaling, etc. This paper is aimed at proposing a face recognition technique with high accuracy. It focuses on face recognition based on improved SIFT algorithm. In the proposed approach, the face features are extracted using a novel multi-kernel function (MKF) based SIFT technique. The classification is done using SVM classifier. Experimental results shows the superiority of the proposed algorithm over the SIFT technique. Evaluation of the proposed approach is done on CVL face database and experimental results shows that the proposed approach has a recognition rate of 99%.
Now days, the task of face recognition is widely used application of image analysis as well as pattern recognition. In biometric area of the research, automatically face & face expression recognition attracts researcher’s interest. For classifying facial expressions into different categories, it is necessary to extract important facial features which contribute in identifying proper and particular expressions. Recognition and classification of human facial expression by computer is an important issue to develop automatic facial expression recognition system in vision community. In this paper the facial expression recognition system is proposed.
ENHANCING THE HUMAN EMOTION RECOGNITION WITH FEATURE EXTRACTION TECHNIQUESIAEME Publication
Human emotions are states of mental health that resolve spontaneously rather than through conscious exertion, and are accompanied by physiological changes in the facial muscles that signify expressions. Nonverbal communication methods such as expressions, eye movements, and gestures are used in many applications of human computer interaction. Identifying emotions is not an easy task because there is no difference between the emotions of a face, and there is also a lot of complexity and variability. The machine learning algorithm uses some open features to model the face. Automatic emotion recognition based on facial expression is an interesting research field, which has presented and applied in several areas such as safety, health and in human machine interfaces. Researches in this field are interested in developing techniques to interpret, code facial expressions and extract these features in order to have a better prediction by computer. Machine learning, one of the top emerging sciences, has an extensive range of applications. In this paper, the optimization techniques-based feature extraction techniques are used to enhance the recognition of the human emotion using facial images. The optimization techniques like Ant Colony Optimization, Particle Swarm Optimization, Genetic Algorithm are used. Various metrics are used to evaluate the performance of the feature extraction techniques for emotion recognition.
Combining left and right palmprint images for more accurate personal identifi...Shakas Technologies
Multibiometrics can provide higher identificationaccuracy than single biometrics, so it is more suitable forsome real-world personal identification applications that needhigh-standard security. Among various biometrics technologies,palmprint identification has received much attention because ofits good performance.
Combining left and right palmprint images for more accurate personal identifi...LogicMindtech Nologies
IMAGE PROCESSING Projects for M. Tech, IMAGE PROCESSING Projects in Vijayanagar, IMAGE PROCESSING Projects in Bangalore, M. Tech Projects in Vijayanagar, M. Tech Projects in Bangalore, IMAGE PROCESSING IEEE projects in Bangalore, IEEE 2015 IMAGE PROCESSING Projects, MATLAB Image Processing Projects, MATLAB Image Processing Projects in Bangalore, MATLAB Image Processing Projects in Vijayangar
Biometrics was developed with the aim of improving the overall security level in all society contexts. A biometric system describes a set of techniques to analyze certain individual's biometric features, store and then using those patterns to identify or verify the identity of a person. The palmprint contains not only principal curves and wrinkles but also rich texture and miniscule points, so the palmprint identification is able to achieve a high accuracy because of available rich information in palmprint. Various palmprint identification methods, such as coding based methods and principal curve methods have been proposed in past decades. In addition to these methods, subspace based methods can also perform well for palmprint identification. Combining the left and right palmprint images to perform multibiometrics is easy to implement and can obtain better results.
Multimodal biometrics can provide higher identification accuracy than single or unimodal biometrics, so it is more suitable for some real-world personal identification applications that need high-standard security. A onetime password is included for higher security and accuracy.
One time passwords generally expire after using once. They are generated for using it within a certain time period after which it is useless. These passwords are set as a secondary security measure for the primary palmprint recognition.
Combining left and right palmprint images forjpstudcorner
To get this project in ONLINE or through TRAINING Sessions,
Contact:JP INFOTECH, Old No.31, New No.86, 1st Floor, 1st Avenue, Ashok Pillar, Chennai -83. Landmark: Next to Kotak Mahendra Bank. Pondicherry Office: JP INFOTECH, #45, Kamaraj Salai, Thattanchavady, Puducherry -9. Landmark: Next to VVP Nagar Arch. Mobile: (0) 9952649690 , Email: jpinfotechprojects@gmail.com, web: www.jpinfotech.org Blog: www.jpinfotech.blogspot.com
Fiducial Point Location Algorithm for Automatic Facial Expression Recognitionijtsrd
We present an algorithm for the automatic recognition of facial features for color images of either frontal or rotated human faces. The algorithm first identifies the sub images containing each feature, afterwards, it processes them separately to extract the characteristic fiducial points. Then Calculate the Euclidean distances between the center of gravity coordinate and the annotated fiducial points coordinates of the face image. A system that performs these operations accurately and in real time would form a big step in achieving a human like interaction between man and machine. This paper surveys the past work in solving these problems. The features are looked for in down sampled images, the fiducial points are identified in the high resolution ones. Experiments indicate that our proposed method can obtain good classification accuracy. D. Malathi | A. Mathangopi | Dr. D. Rajinigirinath ""Fiducial Point Location Algorithm for Automatic Facial Expression Recognition"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd21754.pdf
Paper URL: https://www.ijtsrd.com/computer-science/data-miining/21754/fiducial-point-location-algorithm-for-automatic-facial-expression-recognition/d-malathi
REVIEW OF FACE DETECTION SYSTEMS BASED ARTIFICIAL NEURAL NETWORKS ALGORITHMSijma
Face detection is one of the most relevant applications of image processing and biometric systems.
Artificial neural networks (ANN) have been used in the field of image processing and pattern recognition.
There is lack of literature surveys which give overview about the studies and researches related to the using
of ANN in face detection. Therefore, this research includes a general review of face detection studies and
systems which based on different ANN approaches and algorithms. The strengths and limitations of these
literature studies and systems were included also.
Review of face detection systems based artificial neural networks algorithmsijma
Face detection is one of the most relevant applications of image processing and biometric systems.
Artificial neural networks (ANN) have been used in the field of image processing and pattern recognition.
There is lack of literature surveys which give overview about the studies and researches related to the using
of ANN in face detection. Therefore, this research includes a general review of face detection studies and
systems which based on different ANN approaches and algorithms. The strengths and limitations of these
literature studies and systems were included also.
Efficient Facial Expression and Face Recognition using Ranking MethodIJERA Editor
Expression detection is useful as a non-invasive method of lie detection and behaviour prediction. However, these facial expressions may be difficult to detect to the untrained eye. In this paper we implements facial expression recognition techniques using Ranking Method. The human face plays an important role in our social interaction, conveying people's identity. Using human face as a key to security, the biometrics face recognition technology has received significant attention in the past several years. Experiments are performed using standard database like surprise, sad and happiness. The universally accepted three principal emotions to be recognized are: surprise, sad and happiness along with neutral.
Efficient Face Expression Recognition Methods FER A Literature Reviewijtsrd
Recognition of artificial faces is an intriguing and testing problem and affects important applications in various regions, such as cooperation between human computers and data oriented activity. Facial expression is the fastest correspondence methods for transmitting data. It is straightforward the outward appearance of an individual by looking at his her face yet somehow or other with regard to machines it ends up difficult to pass judgment on the outward appearance while using PC devices yet it is not incomprehensible in any way. This not only revealed any individuals affectability or sentiments, but it can also be used to make a judgement on the psychological views, yet again it could not fully understand the perception of human behaviour, the discovery of mental problems and fabricated human expressions. Expressions such as SAD, HAPPY, DISGUST, FEAR, ANGER, NEUTRAL and SURPRISE have been suggested in a broad range of processesThis paper includes implementing face recognition along with facial expression recognition, analyzing recent and past research to extract effective and efficient methods for recognition of facial expression. Sheena Gaur | Shashi Kant Sharma | Lovendra Solanki | Firdos Alam Sheikh | Ahsan Z Rizvi "Efficient Face Expression Recognition Methods (FER): A Literature Review" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd28026.pdfPaper URL: https://www.ijtsrd.com/computer-science/other/28026/efficient-face-expression-recognition-methods-fer-a-literature-review/sheena-gaur
Face Recognition plays a major role in Biometrics. Feature selection is a measure issue in face
recognition. This paper proposes a survey on face recognition. There are many methods to extract face
features. In some advanced methods it can be extracted faster in a single scan through the raw image and
lie in a lower dimensional space, but still retaining facial information efficiently. The methods which are
used to extract features are robust to low-resolution images. The method is a trainable system for selecting
face features. After the feature selection procedure next procedure is matching for face recognition. The
recognition accuracy is increased by advanced methods.
Multi-View Algorithm for Face, Eyes and Eye State Detection in Human Image- S...IJERA Editor
For fatigue detection such as in the application of driver‟s fatigue monitoring system, the eye state analysis is one of the important and deciding steps to determine the fatigue of driver‟s eyes. In this study, algorithms for face detection, eye detection and eye state analysis have been studied and presented as well as an efficient algorithm for detection of face, eyes have been proposed. Firstly the efficient algorithm for face detection method has been presented which find the face area in the human images. Then, novel algorithms for detection of eye region and eye state are introduced. In this paper we propose a multi-view based eye state detection to determine the state of the eye. With the help of skin color model, the algorithm detects the face regions in an YCbCr color model. By applying the skin segmentation which normally separates the skin and non-skin pixels of the images, it detects the face regions of the image under various lighting and noise conditions. Then from these face regions, the eye regions are extracted within those extracted face regions. Our proposed algorithms are fast and robust as there is not pattern match.
PARTIAL MATCHING FACE RECOGNITION METHOD FOR REHABILITATION NURSING ROBOTS BEDSIJCSES Journal
In order to establish face recognition system in rehabilitation nursing robots beds and achieve real-time
monitor the patient on the bed. We propose a face recognition method based on partial matching Hu
moments which apply for rehabilitation nursing robots beds. Firstly we using Haar classifier to detect
human faces automatically in dynamic video frames. Secondly we using Otsu threshold method to extract
facial features (eyebrows, eyes, mouth) in the face image and its Hu moments. Finally, we using Hu
moment feature set to achieve the automatic face recognition. Experimental results show that this method
can efficiently identify face in a dynamic video and it has high practical value (the accuracy rate is 91%
and the average recognition time is 4.3s).
FACE DETECTION AND FEATURE EXTRACTION FOR FACIAL EMOTION DETECTIONvivatechijri
: Facial emotion Recognition has been a major issue and an advanced area of research in the field of HumanMachine Interaction and Image Processing. To get facial expression the system needs to meet a variety of human facial
features such as color, body shape, reflection, posture, etc. To get a person's facial expression first it is necessary to get
various facial features such as eye movement, nose, lips, etc. and then differentiate by comparing the trained data using
differentiation appropriate for speech recognition. An AI-based approach to the novel visual system system is suggested.
There are two main processes in the proposed system, namely Face detection and feature extraction.Face detection is
performed using the Haar Cascade Method. The proper feature extraction method is used to extract the element and then
used a vector machine to distinguish the final face shape. The FER13 data set is used for training.
Face expression recognition using Scaled-conjugate gradient Back-Propagation ...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
Review of facial expression recognition system and used datasetseSAT Journals
Abstract The human face is main part to recognize the individuals as well as provides the important information, current state of user behavior through their different expressions. Therefore, in biometric area of the research, automatically face & face expression recognition attracts researcher’s interest. The other areas which use such technique are computer science medicine, psychology etc. Usually face recognition system is consisting of many internal tasks. Face detection is thefirst task of such systems. Due to different variations across the human faces, the process of detecting face becomes complex. But with help of different modeling methods, it becomes possible to recognize the face and hence different face expressions. This paperpresents a literature review over the techniques and methods used for facial expression recognition. Also, different facial expression datasets available for the research or testing of existing methods of facial expression recognition are discussed. Keywords: Facial Expression, Face Detection, Features Extraction, Recognition, datasets.
Similar to Automatic AU intensity detection/estimation for Facial Expression Analysis: A Review (20)
Exploring the Experiences of Gender-Based Violence
and The Associated Psychosocial and Mental Health
Issues of Filipino HIV-Positives: Implications for
Psychological Practice
Evangeline R Castronuevo-Ruga1, Normita A Atrillano2
Abstract: The phenomenon of gender-based violence has generated attention from research practitioners and helping professionals since
the surge of the women’s movement three or so decades ago in the Philippines. At about the same time, the HIV-AIDS gained similar
attention with the disclosure of the first ever case of the country in the mid-80s. Only recently, however, has the intersectionality of these
two phenomena been looked into by the research community in other countries and has yet to see parallel response locally. This research,
therefore, attempts to map out the lived experiences of People Living with Human Immuno Deficiency Virus (PLHIV) who have undergone
gender-based violence (GBV). It specially looks into the consequent psychosocial and mental health issues. Using focus group discussion with
24 purposively sampled participants from the highly vulnerable groups based in three major Philippine cities, thematic analysis reveals that
the participants experienced various forms of gender-based violence, e.g., sexual, emotional/psychological, economic, verbal, physical) and
expressions of stigma and discrimination, which in turn, led to manifestations of different emotional and psychological trauma, depression,
internalized homophobia, greater health risks and risk-taking behaviours, among others. It might be worthwhile to consider the possibility
that the consequent risk-taking and self-injurious tendencies played a role in their eventual contraction of HIV.
Estimation of Storage-Draft Rate Characteristics of
Rivers in Selangor Region
Farah Syazana Abd Latif1, Siti Fatin Mohd Razali2
1,2Faculty of Engineering & Built Environment, Universiti Kebangsaan Malaysia
Abstract: Drought is a phenomenon of extreme water shortage that has significant economic, social, environmental and human life
impact. Streamflow drought characteristics and properties are useful in the design of hydro-technical projects, water resources planning and
management purposes. Information on low flow magnitude, frequency, probability and return period are very crucial in analysing
streamflow drought at the operational level in public water supply. The objectives of this study are to determine the characteristics of low
flow for every streamflow station in the Selangor region. The estimation of minimum storage draft-rate with the probability of low flow
return periods of 2, 5, 10, 20, and 50 years is presented in this paper.
Awwal-Awwal Tampat Budjang Journey Back to
Pre-Islamic Epoch: A Cultural Semiotic
Helen G Juaini1
Abstract: Cultural background plays a significant role in the sphere of semiotics. Semiotics as a discipline is recognized as a useful tool in
gauging cultural background and identifying signs that might represent the message of a certain work. Given the rich cultural context of
Tawi-Tawi oral literature this can be used in studying semiotics. Semiotic tools were employed to interpret the awwal-awwal as provided by
the respondents and to formulate a subsequent understanding of this oral literature in relation to the Sama’s claim of sacredness of Tampat
Budjang.
Politeness and Intimacy in Application Letters of
Three Cultural Groups in Mindanao
Helen G Juaini1
Abstract: 150 application letters from the three cultural groups in Mindano, namely Sinama, Subanen, and Tausug have been analysed
in a mixed-method design. The focus of the study is on the two features of politeness and intimacy. In the quantitative analysis, the model
proposed by Brown & Levinson (1987) and that of Columns (2005) which have drawn upon the features of indirectness in requesting and
the length of letters as the indicators of politeness are used. In the qualitative and descriptive analysis formality in salutation and opening
clause as well as the use of abbreviated forms are taken into account. The result shows that Tausug use the politest style in their application
letters, followed by Sinama and Subanen respectively. On the other hand, Sinama, Subanen, and Tausug use the least intimate style in their
business letters. The findings are hoped to help better inter-cultural understanding, especially with respect to written rhetorical
characteristics.
New Authentication Algorithm for IoT Environment
based on Non-Commutative Algebra and Its
Implementation
Maki Kihara1, Satoshi Iriyama2
1,2Tokyo University of Science
Abstract: Recently, IoT devices such as robots, speakers, domestic electrical appliances and smart devices are provided everywhere for
everyone. While their authentication request is quite ubiquitously, namely, an authentication for sharing services, the actual
implementations are patchy schemes of variety security policies. In this study, we propose the new authentication scheme for IoT devices
without certificate authority which is fast enough as well as secure. The verification algorithm is based on suitable ciphered metric. We
define a class of such verifiable encryption and give an example for authentication. Moreover, we show the implementation which keeps
perfect secrecy by means of Shannon’s theory.
Developing a Strategic Organisational Learning
Framework to Improve Caribbean Disaster
Management Performance
Joanne Persad1
Abstract: Disasters are social constructs and require an agility and adaptability from national disaster organisations (NDOs). The
environment in which NDOs operate are complex adaptive systems environment, and organisational learning as a key approach is considered
fundamental to strengthening the ability of an NDO to perform at its best. With the potential for loss of lives, the destruction of critical
infrastructure and housing and to the risk of setting back a country’s economic development by many years, learning from the lessons of the
past, to reduce the negative impacts is critical for the onward growth of Caribbean countries which, for the most part, are small island
developing states. The Caribbean Region is the one of the most hazard prone regions in the world (Walbrent College 2012). Lessons from
disaster impacts are identified, gaps are well documented, and failures are sometimes exposed. But learning, in terms of making changes to
improve systems, performance and resilience, is questionable. The lessons must be applied for change to occur, this is part of the knowledge
management process in the context of disaster organisations. The purpose of this study is to explore the apparent inability of national
disaster organizations in the Caribbean to apply the lessons learnt from previous disasters. Three (3) Caribbean countries have been selected
for this research. It is a multiple case study where the unit of analysis is the national disaster organisation. This study is based on an
interpretive paradigm.
Combating Climate Change and Land Degradation in
The West African Sahel: A Multi-Country Study of
Mali, Niger and Senegal
S A Igbatayo1
1Head, Department of Economics & Management Studies, AFE Babalola University, Nigeria
Abstract: The West African Sahel is a vast ecological zone separating the Sahara Desert to the north and Sudanian savannah to the
south; traversing Senegal, Mali, Burkina Faso, Niger, northern Nigeria and Chad. With a population estimated at more than 60 million
people, the region features a multiplicity of development challenges. It is home to some of the world’s most impoverished people, whose
livelihoods are mostly reliant on rain-fed agriculture. Characterized by semi-arid vegetation, the West African Sahel is one of the most
environmentally degraded ecosystems in the world. The region faces severe and recurring bouts of droughts since the 1980s, jeopardizing
environmental sustainability. During the past four decades, the West African Sahel has witnessed below-average annual precipitation, with
two severe drought periods in 1972-1973 and 1983–1984, in a development that undermined agricultural productivity and spawned
severe land degradation. Various studies have predicted even more severe climate variability and change in the region, with drier and more
frequent dry periods expected. The intergovernmental Panel on climate change (IPCC, 2007) revealed a decline in annual rainfall in West
Africa since the end of the 1960s, with a reduction of 20% to 40% observed in the periods 1931-1960 and 1968–1990. Repeated
droughts, fuelled by climate change, have undermined land productivity, turning arable soils into marginal lands, and rendering land
resources vulnerable to such anthropogenic activities as over-grazing, agricultural intensification and deforestation, which are common
practices across the region. The major objective of this paper is to shed light on climate change and land degradation patterns in the West
African Sahel. It employs empirical data to analyse the trends, with particular emphasis on Mali, Niger and Senegal. The study reveals
considerable threats posed by the twin scourges of climate change and land degradation to food security, environmental sustainability and
regional stability.
Combating Climate Change and Land Degradation in
The West African Sahel: A Multi-Country Study of
Mali, Niger and Senegal
S A Igbatayo1
1Head, Department of Economics & Management Studies, AFE Babalola University, Nigeria
Abstract: The West African Sahel is a vast ecological zone separating the Sahara Desert to the north and Sudanian savannah to the
south; traversing Senegal, Mali, Burkina Faso, Niger, northern Nigeria and Chad. With a population estimated at more than 60 million
people, the region features a multiplicity of development challenges. It is home to some of the world’s most impoverished people, whose
livelihoods are mostly reliant on rain-fed agriculture. Characterized by semi-arid vegetation, the West African Sahel is one of the most
environmentally degraded ecosystems in the world. The region faces severe and recurring bouts of droughts since the 1980s, jeopardizing
environmental sustainability. During the past four decades, the West African Sahel has witnessed below-average annual precipitation, with
two severe drought periods in 1972-1973 and 1983–1984, in a development that undermined agricultural productivity and spawned
severe land degradation. Various studies have predicted even more severe climate variability and change in the region, with drier and more
frequent dry periods expected. The intergovernmental Panel on climate change (IPCC, 2007) revealed a decline in annual rainfall in West
Africa since the end of the 1960s, with a reduction of 20% to 40% observed in the periods 1931-1960 and 1968–1990. Repeated
droughts, fuelled by climate change, have undermined land productivity, turning arable soils into marginal lands, and rendering land
resources vulnerable to such anthropogenic activities as over-grazing, agricultural intensification and deforestation, which are common
practices across the region. The major objective of this paper is to shed light on climate change and land degradation patterns in the West
African Sahel. It employs empirical data to analyse the trends, with particular emphasis on Mali, Niger and Senegal. The study reveals
considerable threats posed by the twin scourges of climate change and land degradation to food security, environmental sustainability and
regional stability. It also presents a policy framework underpinned by climate change mitigation and adaptation strategies, formalizing land
rights for farmers, subsidizing farm inputs, creating grazing reserves for pastoralists and deepening poverty reduction strategies.
A Study on Factor Affecting Textile
Entrepreneurship – A Special Emphasis on Tirupur
District
P Anbuoli1
1Assistant Professor, Department of Business Administration, Mannar Thirumalai Naicker College, India
Abstract: Entrepreneurial success depends on various factors associated with the business, the entrepreneurs’ wishes to start. Entrepreneurs
need some sort of inspirations to succeed in their business ventures. Being a versatile industry, textile attracts many entrepreneurs both urban
and rural peoples and requires minimal investment to start. Textile entrepreneurs have to face several challenges and prospects associated
with their business. This study has been commenced with the objectives to check demographic profile, factors affecting textile entrepreneurs,
encouragement of external factors and personal reason behind to become textile business entrepreneurs. This study has been carried out with
100 textile entrepreneurs; the sample has been selected by using simple random sampling. This study is also carried out with non-disguised
and structured questionnaire; which consists of four parts with seeking information on demographic profile, factors affecting textile
entrepreneurs, external encouraging factors and personal reason to become textile entrepreneurs. This study uses percentage analysis, factor
analysis, Garrett score ranking, and t-test to analyse the data collected. It was concluded that textile entrepreneurs have been encouraged by
various factors and moreover several factors significantly affect their business.
Factors Affecting Consumer Purchase Behaviour
towards Online Clothing Products in Bangladesh
T Islam1
1BRAC Business School, BRAC University, Dhaka, Bangladesh
Abstract: The online clothing businesses have seen a considerable rise in recent times, with a high and growing demand. The purpose of
this study is to determine the factors that play significant roles in creating purchase intention towards the online clothing products in
Bangladesh. Secondary research was used to build the model of customer purchase intention. A structured questionnaire was employed to
gather data and test the model. Factor analysis and regression were used to test the model. The regression model suggested that customer
purchase intention was induced most by the online marketing activities of the online retailers, followed by pricing strategy implemented and
sense of security provided (in that order). To understand customer purchase intentions better, it may be important to look at additional
factors or seek better measures of the constructs. The study suggests that online retailers should heavily focus on online promotions and
pricing.
Improvement Measures on Wage System of
Construction Skilled Worker in South Korea
Kun-Hyung Lee1, Byung-Uk Jo2, Kyeoung-Min Han3, Chang-Baek Son4
1,2,3Graduate, School of Architectural Engineering, Semyung University, Jecheon-si, South Korea
4Professor, Department of Architectural Engineering, Semyung University, Jecheon-si, South Korea
Abstract: Unlike other industries, the construction industry is characterized by its heavy dependence on labour force with most work done
by workers. Still, the industry is witnessing the declining influx of young workers and the rising turnover rates of skilled workers due to such
issues as the advancement of 3D industry, negative image and absence of an established wage system. Hence, this paper proposes an
alternative scheme that would help improve the wage system and work environment for skilled construction workers in Korea.
Mastering the Recycling of Masonry while building
Tadao Ando’s Private Gallery in Lincoln Park,
Chicago
Daniel Joseph Whittaker1
Abstract: The notion of a great presence of masonry rarely conjures up the likes of buildings by master architect, Tadao Ando san of
Osaka, Japan, who is better known for his sublime shaping of space with planar forms of site-cast concrete. Perhaps though, one may recall
the ‘historical intervention’ on a grand scale—the now nine-year-old Punta Della Dogan a project (2009) in Venice, Italy, as prima facie
evidence of his dialogue with a vast quantity of ancient masonry in the Laguna. However, a new project by Ando, recently opened in
Chicago, Illinois (October 2018), presents the private-museum-gallery-going public with a new North American delight. Here, the senses
are able to indulge in a hybrid set of experiences shaped by masonry, concrete, and white painted plaster surfaces. This paper explores how
the modern concrete master has expanded his dynamic architectural vocabulary utilizing what is known as Chicago common brick: a soft,
Lake Michigan-sand and clay based fired brick, and incorporated it into his most recent private commission located in Lincoln Park,
Chicago.
RRI Buffer Based Energy and Computation Efficient
Cache Replacement Algorithm
Muhammad Shahid1
1Computer Science Department, National University of Computer and Emerging Sciences, Islamabad
Abstract: Energy consumption is an important factor of com-mutational power these days. Large scale energy consumption results in bad
system performance and high cost. To access frequently used data, we place it in Cache. Cache provides us opportunity to access that data in
a small time. Cache memory helps in retrieving data in minimum time improving the system performance and reducing power consumption.
Due to limited size of Cache, replacement algorithms used to make space for new data. There are many existing cache replacement
algorithms for example LRU, LFU, MRU, FIFO etc. Existing algorithms consume a lot of energy while replacing cold blocks of data.
Replacement algorithms are usually designed to reduce miss rate and increase hit rate. These algorithms replace cold blocks (not going to use
in future) and due to large number of cold blocks, they consume lot of energy. This paper proposes an energy and computation efficient cache
replacement algorithm that put only hot blocks in action instead of removing cold blocks. This paper also discusses different replacement
algorithms proposed in different papers and compare these algorithms on basis of different parameters mainly energy consumption. In our
experiments we have found LRU and FIFO as best replacement algorithms for Increased hit rates and Energy efficiency respectively.
Key Performance Index of Increasing Air Quality
with Construction Schedule Control
Hyoung-Chul Lim1, Dongheon Lee2, Dong-Eun Lee3, Daeyoung Kim4
1Professor, 2Doctorial Course, School of Architectural Engineering, Changwon National University, Korea
3Professor, School of Architecture & Civil Engineering, Kyungpook National University, Korea
4Professor, Department of Architecture, Kyungnam University, Korea
Abstract: Recently, air quality in residential spaces has been major concern. In particular, the indoor air quality of residential facility
before occupancy, which is related to the interior material, is a serious problem. existing research has mainly focused on pollution control
after construction, but this research has derived I key performance index I about increasing air quality and priority of management with a
controlling schedule. That is the objectives of research. The results show the relative priority of the four major items in wall‐based apartment
buildings and in column‐based apartment buildings. An analysis of the parties responsible for improvement based on the IAQ results shows
more efforts to improve IAQ are needed in material factories and engineering/design companies.
Exploring Revitalization Solutions: Engaging
Community through Media Architecture
Behzad Shojaedingivi1
1University of Tehran
Abstract: This paper aims to investigate Media Architecture and its potentials for culturally based revitalization. Media Architecture
presents a new approach based on Augmentation concepts, in which projects are designed and implemented adopting contemporary mediums
in an aesthetic way in order to attract the presence of a more cultural audience and increase the participation of the local residents.
Ultimately this will lead to an increase of interaction between different classes in neglected areas and strengthen their connection to their
built environment. This is an interdisciplinary approach in which architecture and contemporary mediums are combined aesthetically with
the aim of creating revival solutions in neglected areas.
Criteria of Creating Social Interaction for Green
Open Space in Karkh, Iraq
Sarah Abdulkareem Salih1, Sumarni Ismail2
1Master Student, 2Lecturer, Department of Architecture, Universiti Putra Malaysia, Malaysia
Abstract: This paper outlines the issue on open spaces, which led to decrease social interaction among residents in Baghdad city
nowadays. The main objective of the paper is to identify the criteria of green open spaces to achieve sound social interaction in Baghdad city,
Iraq. This paper employed quantitative method, in the form of survey, for data collection. Data were obtained from questionnaires, through
the selection of 270 respondents in a single-stage random procedure from ten specific neighbourhoods in Karkh district. The study findings
confirm that open spaces and parks is essential to enhance social interaction by implementing appropriate criteria in that open spaces or
parks. The results of this study are useful reference for urban and landscape planners, architects, social psychologists, the Municipality of
Baghdad, and researchers in this field.
The CoreConferences 2019 held on 20th – 21st March, 2019, in collaboration with Association of Scientists, Developers and Faculties (ASDF), an International body, at Taipei, Taiwan. CoreConferences 2019 provides a chance for Academic and Industry professionals to discuss the recent progress in the area of Multiple. The outcome of the conference will trigger for the further related research and future technological improvement. This conference highlights the novel concepts and improvements related to the research and technology.
ICCOTWT 2018 will be the most comprehensive conference focused on the various aspects of Cloud of Things and Wearable Technologies. This Conference provides a chance for academic and industry professionals to discuss recent progress in the area of Cloud of Things and Wearable Technologies. Furthermore, we expect that the conference and its publications will be a trigger for further related research and technology improvements in this important subject.
The goal of this conference is to bring together the researchers from academia and industry as well as practitioners to share ideas, problems and solutions relating to the multifaceted aspects of Cloud of Things and Wearable Technologies.
The International Conference on Computer, Engineering, Law, Education and Management (ICCELEM 2017)” held on 28 - 29th September 2017, in collaboration with Association of Scientists, Developers and Faculties (ASDF), an International body, at The Westin Chosun Seoul, Seoul, South Korea.
The Third International Conference on “Systems, Science, Control, Communication, Engineering and Technology (ICSSCCET 2017)” held on 16 - 17th February 2017, in collaboration with Association of Scientists, Developers and Faculties (ASDF), an International body, at Teegala Krishna Reddy Engineering College, Hyderabad, India, Asia.
The First International Conference on “Advanced Innovations in Engineering and Technology (ICAIET 2017)” held on 14th - 15th Feb 2017, in collaboration with Association of Scientists, Developers and Faculties (ASDF), an International body, at Rohini College of Engineering and Technology, Tamilnadu, India, Asia.
The First International Conference on “Intelligent Computing and Systems (ICICS 2017)” held on 13th - 14th February 2017, in collaboration with Association of Scientists, Developers and Faculties (ASDF), an International body, at NSN College of Engineering and Technology, Karur, Tamilnadu, India, Asia.
The First International Conference on “Advances & Challenges in Interdisciplinary Engineering and Management 2017 (ICACIEM 2017)” held on 11 – 12th February 2017, in collaboration with Association of Scientists, Developers and Faculties (ASDF), an International body, at Vidyaa Vikas College of Engineering and Technology, Tiruchengode, Tamilnadu, India, Asia.
Wireless sensor networks can provide low cost solution accompanied with limited storage, computational capability and power for verity of real-world problems and become essential factor when sensor nodes are arbitrarily deployed in a hostile environment. The cluster head selection technique is also one of the good approaches to reduce energy consumption in wireless sensor networks. The lifetime of wireless sensor networks is extended by using the uniform cluster head selection and balancing the network loading among the clusters. We have reviewed various energy efficient schemes apply in WSNs of which we concentrated on selection of cluster head approach and proposed an new method called Sleep Scheduling Routing with in clusters for Energy Efficient [SSREE]in which some nodes in clusters are usually put to sleep to conserve energy, and this helps to prolong the network lifetime. EASSR selects a node as a cluster head if its residual energy is more than system average energy and have less energy consumption rate in previous round. Then, an Performance analysis and compared statistic results of SSREE shows of the significant improvement over existing protocol LEACH, SEP and M-GEAR protocol in terms of lifetime of network and data units gathered at BS.
Due to rapid urbanization the manufacturing processes of conventional building materials pollutes air, water and land. Hence in order to fulfil the increasing demand it is required to adopt a cost effective, eco-friendly technologies by improving the traditional techniques with the usage of available local materials. Agro – industrial and other solid waste disposal is another serious issue of concern in most of developing countries. The present paper explores the potential application of agro-waste as an ingredient for alternate sustainable construction materials.
There has been an ever-increasing interest in big data due to its rapid growth and since it covers diverse areas of applications. Hence, there seems to be a need for an analytical review of recent developments in the big data technology. This paper aims to provide a comprehensive review of the big data state of the art, conceptual explorations, major benefits, and research challenging aspects. In addition to that, several future directions for big data research are highlighted.
A correct node operation and power administration are significant issues in the wireless sensor network system. Ultrasonic, dead reckoning, and radio frequency information is obtained by using localization mechanism and worked through a specific filter algorithm. In this paper, a well-organized grid deployment method is applied to split the nodes into multiple individual grids. The tiny grids are used for improved resolution and bigger grids are used to decrease the complexity of processing. The efficiency of each grid is obtained by environmental factors such as redeployed nodes, boundaries, and obstacles. To decrease the power usage, asynchronous power management method is designed. In network communication, power management method is applied by using an asynchronous awakening scheme and n-duplicate coverage algorithm is engineered for the coverage of nodes.
More from Association of Scientists, Developers and Faculties (20)
The use of Nauplii and metanauplii artemia in aquaculture (brine shrimp).pptxMAGOTI ERNEST
Although Artemia has been known to man for centuries, its use as a food for the culture of larval organisms apparently began only in the 1930s, when several investigators found that it made an excellent food for newly hatched fish larvae (Litvinenko et al., 2023). As aquaculture developed in the 1960s and ‘70s, the use of Artemia also became more widespread, due both to its convenience and to its nutritional value for larval organisms (Arenas-Pardo et al., 2024). The fact that Artemia dormant cysts can be stored for long periods in cans, and then used as an off-the-shelf food requiring only 24 h of incubation makes them the most convenient, least labor-intensive, live food available for aquaculture (Sorgeloos & Roubach, 2021). The nutritional value of Artemia, especially for marine organisms, is not constant, but varies both geographically and temporally. During the last decade, however, both the causes of Artemia nutritional variability and methods to improve poorquality Artemia have been identified (Loufi et al., 2024).
Brine shrimp (Artemia spp.) are used in marine aquaculture worldwide. Annually, more than 2,000 metric tons of dry cysts are used for cultivation of fish, crustacean, and shellfish larva. Brine shrimp are important to aquaculture because newly hatched brine shrimp nauplii (larvae) provide a food source for many fish fry (Mozanzadeh et al., 2021). Culture and harvesting of brine shrimp eggs represents another aspect of the aquaculture industry. Nauplii and metanauplii of Artemia, commonly known as brine shrimp, play a crucial role in aquaculture due to their nutritional value and suitability as live feed for many aquatic species, particularly in larval stages (Sorgeloos & Roubach, 2021).
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/
Salas, V. (2024) "John of St. Thomas (Poinsot) on the Science of Sacred Theol...Studia Poinsotiana
I Introduction
II Subalternation and Theology
III Theology and Dogmatic Declarations
IV The Mixed Principles of Theology
V Virtual Revelation: The Unity of Theology
VI Theology as a Natural Science
VII Theology’s Certitude
VIII Conclusion
Notes
Bibliography
All the contents are fully attributable to the author, Doctor Victor Salas. Should you wish to get this text republished, get in touch with the author or the editorial committee of the Studia Poinsotiana. Insofar as possible, we will be happy to broker your contact.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
hematic appreciation test is a psychological assessment tool used to measure an individual's appreciation and understanding of specific themes or topics. This test helps to evaluate an individual's ability to connect different ideas and concepts within a given theme, as well as their overall comprehension and interpretation skills. The results of the test can provide valuable insights into an individual's cognitive abilities, creativity, and critical thinking skills
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
ESR spectroscopy in liquid food and beverages.pptxPRIYANKA PATEL
With increasing population, people need to rely on packaged food stuffs. Packaging of food materials requires the preservation of food. There are various methods for the treatment of food to preserve them and irradiation treatment of food is one of them. It is the most common and the most harmless method for the food preservation as it does not alter the necessary micronutrients of food materials. Although irradiated food doesn’t cause any harm to the human health but still the quality assessment of food is required to provide consumers with necessary information about the food. ESR spectroscopy is the most sophisticated way to investigate the quality of the food and the free radicals induced during the processing of the food. ESR spin trapping technique is useful for the detection of highly unstable radicals in the food. The antioxidant capability of liquid food and beverages in mainly performed by spin trapping technique.
2. International Conference on Inter Disciplinary Research in Engineering and Technology 84
Cite this article as: Neeru Rathee, Nishtha. “Automatic AU intensity detection/estimation for Facial
Expression Analysis: A Review”. International Conference on Inter Disciplinary Research in Engineering
and Technology (2016): 83-88. Print.
To make the AU detection more robust and more efficient, we deal in both frontal-view and profile-view as some AUs like puckering
of lips or pushing of jaws forward are not clearly detectable in frontal view, but are clearly observable in profile view as these AUs
represent out-of-image plane non-rigid face movements whereas movement of the eyebrows and changes in appearance of the eye
cannot be detected in profile view but are easily observable in frontal facial view. Moreover, this is one of the major step to establish a
technological framework for automatic AU detection from multiple views of the face [12, 13].
Automatic recognition of AUs can be done on appearance-based features, geometric features or both. Appearance-based approach uses
example images called templates of the face to perform recognition and feature extraction. It includes selecting the best set of Gabor
wavelet filter, using AdaBoost and train Support Vector Machine (SVM) to classify AUs. Geometric-feature-based approach method works
on shape or deformation of facial features such as position or velocities of facial fiducial points or the distance between these points.
Geometric-based approach involves automatically detecting n- facial points and use a facial point tracker based on particle filtering with
factorized likelihoods to track these points [8, 9, 10].
Current challenges in AU detection are face occlusion, glasses, facial hair and rigid head movements, that occur in real-world
frequently. Out-of-plane head movements also lead to self-occlusion of face. As AUs are more localized in the face than expressions of
emotions the problem of occlusion is much bigger in AUs as compared to emotions [11, 12]. The problem of rigid head movement can
be solved by using head-mounted cameras which in turn reduces the freedom of movement of the subject making it uncomfortable for
the subject. The intensity of AUs and its temporal phase transition (onset, apex, and offset) detection is still a area of concern. The
solution to the above mentioned concern will result in detection of complex as well as higher level behaviour deception, cognitive
states like agreement (disagreement), and psychological states like pain [12]. Moreover, the proposed methods so far are not able to
encode all the 44 AUs defined in FACS, simultaneously.
The presented survey focuses on feature extraction and classification for AUs detection and estimation that has been adopted by
researchers. The rest of the paper is organised as follows. Section 2 deals with facial expression feature extraction and section 3 gives a
brief idea about all the classification techniques. Section 4 describes the various challenges and future scope in this area of research and
conclusion.
FEATURE EXTRACTION
After the face has been detected in the observed scene, the next step is to extract information about the encountered facial expression.
Feature extraction depends on kind of input image and applied face representation [1]. Three types of face representation are: holistic,
analytic and hybrid. In holistic approach, the face is represented as a whole unit. In analytic face representation, the face is modelled as
a set of facial points or as a set of templates fitted to the facial features such as mouth and eyes. In the hybrid approach the face is
represented as a combination of analytic and holistic approaches i.e. a set of facial points is used to determine an initial position of a
template that models the face. The major challenges faced in feature extraction are variation in size and orientation of the face and
obscuring of the facial features due to facial hair and glasses.
Two types of features that are typically usually used to describe facial expression are: Geometric features and Appearance features.
Based on these features the facial feature extraction techniques can be classified as Geometric-feature-based approach and Appearance-
feature- based approach [2].
Pantic et.al used particle filtering for feature extraction [13, 9, 8] which is a approach to directly detect temporal segments of AUs.
They located and tracked a number of facial fiducial points and extracted temporal features from it. Particle filtering was introduced by
Pitt and Shepard [26]. It became the most used tracking technique due to its ability to deal with noise, occlusion and clutter
successfully. It also adopted to deal with colour-based template tracking and shadow problems [13]. This algorithm has three major
drawbacks: 1) large amount of particles that resulted from sampling from the proposal density might be wasted because they
propagated into areas with small likelihood, 2) A particle might have low likelihood but part of it may be close to correct solution, 3)
finally, the estimation of particle weight does not consider the interdependence between the different parts of α (where α is the state
of a temporal event to be tracked) [10, 3].
Later, Patras and Pantic introduced Particle filtering with factorized likelihoods (PFFL) [27] as an extension to this auxiliary particle
filtering theory to address all the afore-mentioned problems inherent in particle filtering. PFFL addresses the problem of
interdependencies between the different parts of state α by assuming that the state α can be partitioned into α such as α = {αଵ…..
α}. PFFL tracking system can be divided into two stages. In the initial stage each facial point i is tracked independently from other
facial points for each frame individually. In the latter stage, interdependence between the sub states are taken into account using
proposal distribution g(α) which is product of posteriors of each α[ 20, 3, 10, 25].
Another Geometric-feature-based approach that is popularly accepted is Active Appearance Model (AAM) and its derivates to
track a dense set of facial points. The location of these points helps us to infer the facial features and their shapes to classify the facial
expression. Sung and Kim used Stereo Active Appearance Model (STAAMs) to track facial points in 3-D videos, as it improves the
3. International Conference on Inter Disciplinary Research in Engineering and Technology 85
Cite this article as: Neeru Rathee, Nishtha. “Automatic AU intensity detection/estimation for Facial
Expression Analysis: A Review”. International Conference on Inter Disciplinary Research in Engineering
and Technology (2016): 83-88. Print.
fitting and tracking of standard AAMs by using multiple cameras to model the 3-D shape and all the rigid motion parameters.
Unfortunately, the approach appears to be promising, but no results on a benchmark database were presented [11].
Appearance-feature- based approach aims to capture skin motion and changes in facial texture due to wrinkles, furrows and
bulge. The various Appearances-feature- based approaches are Gabor features, family of LBP-based detectors (Local Binary Pattern (LBP),
Local Phase Quantization (LPQ))
Gabor wavelet is one of the most famous techniques for facial expression analysis. A Gaussian kernel modulated with a sinusoidal plane
defines a Gabor function. To extract the texture information, filter bank with different characteristic frequencies and orientations is
implemented for feature extraction. The decomposition of an image is computed by filtering it with the filter bank which may include
techniques like applying Gabor filters to the difference image computed by subtracting a neutral expression for each sequence.
Littleworth et.al.[32] applied Gabor filter bank to extract Gabor magnitudes from the whole face and then select the subset of features
using AdaBoost method. The output of the filters selected by AdaBoost is applied to support vector machine for classification of seven
emotion expressions. Gabor features are applied not only for extracting the features in spatial domain but also for temporal domain.
Bartlett et.al.[4] applied Gabor features for simultaneous facial behaviour analysis. BEN JEMAA and KHANFIR [15] used gabor-
coefficients for face recognition. In this geometric distance and gabor-coefficients are used independently or jointly. A gabor-jet vector
is used to characterize the face.
To reduce the dimension of Gabor features, the high-dimensional Gabor features can be uniformly down-sampled. It is observed the
recognition performance get effected by the choice of fiducial points and the down-sampling factor. So, an efficient encoding strategy
for Gabor outputs is needed. Gu et.al. [21] Extended the radial encoding strategy for Gabor outputs to radial grid encoding leading to
high recognition accuracy. This method gives better result than down-sampling method or methods involving Gabor-jet.
LBP introduced by Ojala et al. in [28] has proven to be one of the powerful mean of texture description. The operator works by
creating a label by thresholding a 3x3 neighbourhood of the pixel for every pixel. Ojala et al. later extended the basic LBP to a gray-
scale and rotation invariant texture operator which allows random number of neighbours to be chosen at any point from the central
pixel based on circularly symmetric neighbour set. It reduces the dimensionality of the LBP operator by introducing the concept of
uniform LBP. Uniform LBP consist at most two bit wise transition from zero to one and vice versa and the binary string is considered
circular [11, 29].
The fascinating features of LBP are its illumination tolerance and computational efficiency. LPQ operator was originally proposed by
Ojansivu and Heikkila as a texture descriptor that is robust to image blurring. The descriptor uses 2-D DFT or, more precisely, a
short-term Fourier transform (STFT) computed over a M-by-M neighbourhood to extract local phase information. In real time
application, the neighbouring pixels are highly correlated, leading to dependency between Fourier coefficients, which are quantized in
LPQ. So, Ojansivu et al. introduced a de-correlation mechanism to improve LPQ, which is used by Jiang et al.in [29]. LPQ descriptor
is extended to temporal domain, and the basic LPQ features are extracted from three set of orthogonal planes: XY, ST and YT, where
XT provides spatial domain information, while the XT and YT planes provide temporal information, and is called Local Phase
Quantization from Three orthogonal Planes (LBP-TOP). Zhao et al. [14] applied LBP-TOP to six basic emotions recognition and it is
clearly reported that it outperformed earlier approaches like LBP, Gabor.
FACIAL EXPRESSION CLASSIFICATION
Facial feature extraction is followed by facial expression classification. The classifier classifies the encountered expression either as
facial action or basic emotion or both. The classification depends on template-based, a spatial-based classification method.
Support Vector Machine (SVM) is an excellent classifier in domains such as marine biology, face detection and speech recognition. The
SVM classification is done in the following steps. The selected features instances are divided into two sets: training set and testing set
[30]. A n-fold cross validation loop is employed each time a classifier is trained for search of optimal parameters. While, evaluating
each fold, the training data is split into five sub sets, four of them are used to train a classifier and one is used to test a classifier. SVM is
very well suited for the task of AU detection as the high dimensionality of the feature space has no effect on the training time. SVM
classification can be summarized in three steps: 1) margins of the hyper plane are maximized; 2) the input space is mapped to a linearly
separable feature space; 3) the ‘kernel trick’ is applied [20]. The most frequently used kernel functions are the linear, polynomial, and
Radial Basis Function (RBF) [29].
SVM’s classification performance decreases when the dimensionality of the set is far greater than the training set samples. This can be
handled by decreasing the no. of features used to train SVM which can be done by means of GentleBoost. Littlewort et. al. [32] showed
that an SVM classifier trained using boosting algorithms outperforms both the SVM and the boosting classifier when applied directly.
SVM is used for shape information extraction in [24]. The combination of Adaboost and SVM enhanced both speed and accuracy of the
system.
4. International Conference on Inter Disciplinary Research in Engineering and Technology 86
Cite this article as: Neeru Rathee, Nishtha. “Automatic AU intensity detection/estimation for Facial
Expression Analysis: A Review”. International Conference on Inter Disciplinary Research in Engineering
and Technology (2016): 83-88. Print.
Valstar and Pantic [10, 25] proposed to apply hybrid SVM-HMM (successfully applied for speech recognition) to the problem of AU
temporal model detection. Valstar et.al [20] used Probabilistic Actively learned Support Vector Machine (PAL-SVM) to reduce the
validation time in classifying the AUs displayed in a video. Simon et. al. [31] proposed a segment based SVM, k-seg-SVM which is a
temporal extension to the spatial Bag-of-Words (BoW) approach that was trained with Structured Output SVM (SO-SVM). Recent
research shows that SO-SVMs can outperform other algorithms including HMM, Max-Margin Markov Networks [31]. SO-SVMs have
several benefits in AU detection as : 1) they model the dependencies between visual features and duration of AUs; 2) They can be
trained effectively on all possible segments of the video; 3) No assumption about the underlying structures of the AU are made; 4)
negative examples that are most similar to the AU are selected explicitly.
Rule-based classification method, proposed by Pantic and Rohtkrantz in 2000 classifies the facial expression into the basic emotions
based on previously encoded facial actions. Classification is performed by comparing the AU-coded description of the shown facial
expression with the AU-coded description of the six basic emotional expressions. This classification method gave a recognition rate of
91%. To classify the observed changes in AUs and their temporal segments, these changes are transformed into a set of mid- level
parameters. Six mid-level parameters are defined to describe the change in position of fiducial points. Two midlevel feature
parameters are used to describe the motion of feature points: up/down, in/out (parameters calculated for profile contour fiducial
points). The parameter up/down denotes the upward or downward movement of point P. The parameter in/out denotes the inward
or outward movement of point P. Absent and inc/dec are two midlevel feature parameters used to denote the state of feature points.
Absent denotes the absence of point P in the in profile contour. Inc/dec defines the increase or decrease in distance between two
points. Finally, two midlevel feature parameters: angular and increased_curvature describes two specific shapes formed between
certain feature points. The activation of each AU is divided into three segments, the onset (beginning), the apex, and offset (ending).
Inaccuracies in facial point tracking and occurrences of non-prototypic facial activity result in either unlabeled or incorrectly labelled
temporal segments. This can be handled by using memory-based process that takes into account the dynamics of facial expression i.e.
re-label the current frame/segment from the previous and next frame label according to a rule-based system.
Koelstra and Pantic[6, 7] used GentleBoost classifier on motion from a non-rigid registration combined with HMM. GentleBoost
converges faster than Adaboost and is more reliable in terms of stability. It is used in [22] for feature selection in order to reduce the
dimensionality of of the feature vectors before classification. GentleBoost algorithm selects a linear combination of features one at a
time until the addition of features no longer improves the classification, thus giving a reasonable balance between speed and
complexity. In some AUs the spatial magnitude projection information is not sufficient and temporal domain analysis is needed for AU
classification. Each onset/offset GentleBoost classifier returns a single number per frame which depicts the confidence that the frame
shows the target AU and target temporal segment. To combine onset/offset GentleBoost classifier into a single AU recognizer, a
continuous HMM is used. HMM uses the knowledge of prior probabilities of each temporal segment and duration derived from our
training set. HMM supports a degree of temporal filtering and smooth out the results of the GentleBoost classifiers. However this only
captures the temporal dynamics to a limited degree. This issue can be solved using HMM with state duration model.
Cohen et.al. [33, 34] exploits existing methods and proposes a new architecture of Hidden Markov Models (HMM), in which
segmentation and recognition of facial expression are done automatically. HMM is most commonly used in speech recognition, as
HMM has the ability to model non stationary signals and events. In this all the stored sequences are used to find the best match and
hence this approach is quite time consuming. It works on using the transition probabilities between the hidden states and learns the
conditional probabilities of the observations given the state of the model. The two main model structures used to model expression
are: left-to right and ergodic model. Left-to-right models involves fewer parameters, and thus easier to train. However, it reduces the
degree of freedom of the observation sequence for the model. Ergodic HMM allows more freedom for the model. The main problem
with this approach is that it works on isolated or pre-segmented facial expression sequences that are not available in reality. This
problem is solved using a multi-level HMM classifier. In this, motion features are fed to the emotion specific HMM, then the state
sequence is decoded using a Viterbi algorithm and used as observation vector for the high-level HMM (consist of seven states, one for
each of six emotions and one for neutral).
BEN JEMAA and KHANFIR used non-linear neural networks for classification [15]. The advantages using neural networks for
recognition and classification are the feasibility of training a system in complex conditions like rotation and lighting. The neural
network architecture like number of layers and nodes has to be varied to get good performance. In this study, three types of features
are used namely, 1) Geometric distance between fiducial points, 2) Gabor coefficients, 3) combined information about Gabor
coefficients and Geometric distance. A preliminary version of a two stage classifier combining a kNN-based and ruler based classifier
was first presented by Valaster et.al. in [17] and later used in [18]. Applying only kNN resulted in recognition rates that were lower
than we expected. It was observed that some of the mistakes made by the classifier were deterministic, and can be exploited using a set
of rules based on human FACS coder.
CONCLUSION AND FUTURE SCOPE
Facial expression analysis is an intriguing problem but a need for the future because of its utility in domains of HCI and human
behaviour interpretation. So, a lot of research like feature extraction, classification, pain detection has been done in this area and
results as high as 94.70% [2], 99.98 [15], 94.3 [7] have been attained. But, some areas still need to be explored and can work as a base
5. International Conference on Inter Disciplinary Research in Engineering and Technology 87
Cite this article as: Neeru Rathee, Nishtha. “Automatic AU intensity detection/estimation for Facial
Expression Analysis: A Review”. International Conference on Inter Disciplinary Research in Engineering
and Technology (2016): 83-88. Print.
for any future research. The AUs for basic emotions have been detected by many researcher using different extraction and classification
techniques, but AUs defining complex emotions have not been mentioned very clearly in the research so far. Further research can be
done in area of co-occurrence and interdependence of AUs and detection of AUs for deception as occurrence of complex emotions
generated due to these are more frequent in real time than basic emotions. The facial features have been extracted and classified in
static and video images, but its real-time application has not been explored till now.
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Expression Analysis: A Review”. International Conference on Inter Disciplinary Research in Engineering
and Technology (2016): 83-88. Print.
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