Driver’s drowsiness is one of the major causes of serious accidents in road traffic. Thus, special effort in searching for better assistant technology has been paid. However, several existing approaches fail to work effectively as the head of a drowsy driver is usually in slanting state. Moreover, the shaking of vehicle or the driver’s winking even makes the problem much more complicated. Anyway, head bend posture also signifies a drowsy state. Consequently, this paper proposes a novel approach by considering head nodding behaviour as an input in our detection model. After detecting a human face, some significant facial features are extracted; then, they are used to calculate the predetermined optimal parameters; finally, drowsiness is evaluated based on these thresholds. In our empirical experiments, the proposed algorithm can successfully and accurately detect 96.56% of cases.
Facial Expression Recognition Based on Facial Motion Patternsijeei-iaes
Facial expression is one of the most powerful and direct mediums embedded in human beings to communicate with other individuals’ feelings and abilities. In recent years, many surveys have been carried on facial expression analysis. With developments in machine vision and artificial intelligence, facial expression recognition is considered a key technique of the developments in computer interaction of mankind and is applied in the natural interaction between human and computer, machine vision and psycho- medical therapy. In this paper, we have developed a new method to recognize facial expressions based on discovering differences of facial expressions, and consequently appointed a unique pattern to each single expression.by analyzing the image by means of a neighboring window on it, this recognition system is locally estimated. The features are extracted as binary local features; and according to changes in points of windows, facial points get a directional motion per each facial expression. Using pointy motion of all facial expressions and stablishing a ranking system, we delete additional motion points that decrease and increase, respectively, the ranking size and strenghth. Classification is provided according to the nearest neighbor. In the conclusion of the paper, the results obtained from the experiments on tatal data of Cohn-Kanade demonstrate that our proposed algorithm, compared to previous methods (hierarchical algorithm combined with several features and morphological methods as well as geometrical algorithms), has a better performance and higher reliability.
An efficient feature extraction method with pseudo zernike moment for facial ...ijcsity
Face recognition is one of the most challenging problems in the domain of image processing and machine
vision. Face recognition system is critical when individuals have very similar biometric signature such as
identical twins. In this paper, new efficient facial-based identical twins recognition is proposed according
to the geometric moment. The utilized geometric moment is Pseudo-Zernike Moment (PZM) as a feature
extractor inside the facial area of identical twins images. Also, the facial area inside an image is detected
using Ada Boost approach. The proposed method is evaluated on two datasets, Twins Days Festival and
Iranian Twin Society which contain scaled, which contain the shifted and rotated facial images of identical
twins in different illuminations. The results prove the ability of proposed method to recognize a pair of
identical twins. Also, results show that the proposed method is robust to rotation, scaling and changing
illumination.
Human’s facial parts extraction to recognize facial expressionijitjournal
Real-time facial expression analysis is an important yet challenging task in human computer interaction.
This paper proposes a real-time person independent facial expression recognition system using a
geometrical feature-based approach. The face geometry is extracted using the modified active shape
model. Each part of the face geometry is effectively represented by the Census Transformation (CT) based
feature histogram. The facial expression is classified by the SVM classifier with exponential chi-square
weighted merging kernel. The proposed method was evaluated on the JAFFE database and in real-world
environment. The experimental results show that the approach yields a high recognition rate and is
applicable in real-time facial expression analysis.
ZERNIKE MOMENT-BASED FEATURE EXTRACTION FOR FACIAL RECOGNITION OF IDENTICAL T...ijcseit
Face recognition is one of the most challenging problems in the domain of image processing and machine
vision. The face recognition system is critical when individuals have very similar biometric signature such
as identical twins. In this paper, new efficient facial-based identical twins recognition is proposed
according to geometric moment. The utilized geometric moment is Zernike Moment (ZM) as a feature
extractor inside the facial area of identical twins images. Also, the facial area in an image is detected using
AdaBoost approach. The proposed method is evaluated on two datasets, Twins Days Festival and Iranian
Twin Society which contain scaled and rotated facial images of identical twins in different illuminations.
The results prove the ability of proposed method to recognize a pair of identical twins. Also, results show
that the proposed method is robust to rotation, scaling and changing illumination.
A Novel Mathematical Based Method for Generating Virtual Samples from a Front...CSCJournals
This paper deals with one sample face recognition which is a new challenging problem in pattern recognition. In the proposed method, the frontal 2D face image of each person divided to some sub-regions. After computing the 3D shape of each sub-region, a fusion scheme is applied on sub-regions to create a total 3D shape for whole face image. Then, 2D face image is added to the corresponding 3D shape to construct 3D face image. Finally by rotating the 3D face image, virtual samples with different views are generated. Experimental results on ORL dataset using nearest neighbor as classifier reveal an improvement about 5% in recognition rate for one sample per person by enlarging training set using generated virtual samples. Compared with other related works, the proposed method has the following advantages: 1) only one single frontal face is required for face recognition and the outputs are virtual images with variant views for each individual 2) need only 3 key points of face (eyes and nose) 3) 3D shape estimation for generating virtual samples is fully automatic and faster than other 3D reconstruction approaches 4) it is fully mathematical with no training phase and the estimated 3D model is unique for each individual.
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
Facial Expression Recognition Based on Facial Motion Patternsijeei-iaes
Facial expression is one of the most powerful and direct mediums embedded in human beings to communicate with other individuals’ feelings and abilities. In recent years, many surveys have been carried on facial expression analysis. With developments in machine vision and artificial intelligence, facial expression recognition is considered a key technique of the developments in computer interaction of mankind and is applied in the natural interaction between human and computer, machine vision and psycho- medical therapy. In this paper, we have developed a new method to recognize facial expressions based on discovering differences of facial expressions, and consequently appointed a unique pattern to each single expression.by analyzing the image by means of a neighboring window on it, this recognition system is locally estimated. The features are extracted as binary local features; and according to changes in points of windows, facial points get a directional motion per each facial expression. Using pointy motion of all facial expressions and stablishing a ranking system, we delete additional motion points that decrease and increase, respectively, the ranking size and strenghth. Classification is provided according to the nearest neighbor. In the conclusion of the paper, the results obtained from the experiments on tatal data of Cohn-Kanade demonstrate that our proposed algorithm, compared to previous methods (hierarchical algorithm combined with several features and morphological methods as well as geometrical algorithms), has a better performance and higher reliability.
An efficient feature extraction method with pseudo zernike moment for facial ...ijcsity
Face recognition is one of the most challenging problems in the domain of image processing and machine
vision. Face recognition system is critical when individuals have very similar biometric signature such as
identical twins. In this paper, new efficient facial-based identical twins recognition is proposed according
to the geometric moment. The utilized geometric moment is Pseudo-Zernike Moment (PZM) as a feature
extractor inside the facial area of identical twins images. Also, the facial area inside an image is detected
using Ada Boost approach. The proposed method is evaluated on two datasets, Twins Days Festival and
Iranian Twin Society which contain scaled, which contain the shifted and rotated facial images of identical
twins in different illuminations. The results prove the ability of proposed method to recognize a pair of
identical twins. Also, results show that the proposed method is robust to rotation, scaling and changing
illumination.
Human’s facial parts extraction to recognize facial expressionijitjournal
Real-time facial expression analysis is an important yet challenging task in human computer interaction.
This paper proposes a real-time person independent facial expression recognition system using a
geometrical feature-based approach. The face geometry is extracted using the modified active shape
model. Each part of the face geometry is effectively represented by the Census Transformation (CT) based
feature histogram. The facial expression is classified by the SVM classifier with exponential chi-square
weighted merging kernel. The proposed method was evaluated on the JAFFE database and in real-world
environment. The experimental results show that the approach yields a high recognition rate and is
applicable in real-time facial expression analysis.
ZERNIKE MOMENT-BASED FEATURE EXTRACTION FOR FACIAL RECOGNITION OF IDENTICAL T...ijcseit
Face recognition is one of the most challenging problems in the domain of image processing and machine
vision. The face recognition system is critical when individuals have very similar biometric signature such
as identical twins. In this paper, new efficient facial-based identical twins recognition is proposed
according to geometric moment. The utilized geometric moment is Zernike Moment (ZM) as a feature
extractor inside the facial area of identical twins images. Also, the facial area in an image is detected using
AdaBoost approach. The proposed method is evaluated on two datasets, Twins Days Festival and Iranian
Twin Society which contain scaled and rotated facial images of identical twins in different illuminations.
The results prove the ability of proposed method to recognize a pair of identical twins. Also, results show
that the proposed method is robust to rotation, scaling and changing illumination.
A Novel Mathematical Based Method for Generating Virtual Samples from a Front...CSCJournals
This paper deals with one sample face recognition which is a new challenging problem in pattern recognition. In the proposed method, the frontal 2D face image of each person divided to some sub-regions. After computing the 3D shape of each sub-region, a fusion scheme is applied on sub-regions to create a total 3D shape for whole face image. Then, 2D face image is added to the corresponding 3D shape to construct 3D face image. Finally by rotating the 3D face image, virtual samples with different views are generated. Experimental results on ORL dataset using nearest neighbor as classifier reveal an improvement about 5% in recognition rate for one sample per person by enlarging training set using generated virtual samples. Compared with other related works, the proposed method has the following advantages: 1) only one single frontal face is required for face recognition and the outputs are virtual images with variant views for each individual 2) need only 3 key points of face (eyes and nose) 3) 3D shape estimation for generating virtual samples is fully automatic and faster than other 3D reconstruction approaches 4) it is fully mathematical with no training phase and the estimated 3D model is unique for each individual.
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
AN EFFICIENT FEATURE EXTRACTION METHOD WITH LOCAL REGION ZERNIKE MOMENT FOR F...ieijjournal
Face recognition is one of the most challenging problems in the domain of image processing and machine vision. The face recognition system is critical when individuals have very similar biometric signature such as identical twins. In this paper, the facial area in an image is detected using AdaBoost approach. After that the facial area is divided into some local regions. Finally, new efficient facial-based identical twins feature extractor based on the geometric moment is applied into local regions of face image.The utilized geometric moment is Zernike Moment (ZM) as a feature extractor inside the local regions of facial area of identical twins images. The proposed method is evaluated on two datasets, Twins Days Festival and Iranian Twin Society which contain scaled and rotated facial images of identical twins in different illuminations. The results prove the ability of proposed method to recognize a pair of identical twins.Also, results show that the proposed method is robust to rotation, scaling and changing illumination.
WCTFR : W RAPPING C URVELET T RANSFORM B ASED F ACE R ECOGNITIONcsandit
The recognition of a person based on biological fea
tures are efficient compared with traditional
knowledge based recognition system. In this paper w
e propose Wrapping Curvelet Transform
based Face Recognition (WCTFR). The Wrapping Curve
let Transform (WCT) is applied on
face images of database and test images to derive c
oefficients. The obtained coefficient matrix is
rearranged to form WCT features of each image. The
test image WCT features are compared
with database images using Euclidean Distance (ED)
to compute Equal Error Rate (EER) and
True Success Rate (TSR). The proposed algorithm wit
h WCT performs better than Curvelet
Transform algorithms used in [1], [10] and [11].
This paper describes for a robust face recognition system using skin segmentation technique. This paper addresses the problem of detecting faces in color images in the presence of various lighting conditions. In this paper the face is preprocessed using histogram equalization to avoid illumination problems and then is detected using skin segmentation method. The principal component analysis using neural network is used to recognize the extracted facial features.
Facial landmarking localization for emotion recognition using bayesian shape ...csandit
This work presents a framework for emotion recognition, based in facial expression analysis
using Bayesian Shape Models (BSM) for facial landmarking localization. The Facial Action
Coding System (FACS) compliant facial feature tracking based on Bayesian Shape Model. The
BSM estimate the parameters of the model with an implementation of the EM algorithm. We
describe the characterization methodology from parametric model and evaluated the accuracy
for feature detection and estimation of the parameters associated with facial expressions,
analyzing its robustness in pose and local variations. Then, a methodology for emotion
characterization is introduced to perform the recognition. The experimental results show that
the proposed model can effectively detect the different facial expressions. Outperforming
conventional approaches for emotion recognition obtaining high performance results in the
estimation of emotion present in a determined subject. The model used and characterization
methodology showed efficient to detect the emotion type in 95.6% of the cases.
FACIAL LANDMARKING LOCALIZATION FOR EMOTION RECOGNITION USING BAYESIAN SHAPE ...cscpconf
This work presents a framework for emotion recognition, based in facial expression analysis using Bayesian Shape Models (BSM) for facial landmarking localization. The Facial Action Coding System (FACS) compliant facial feature tracking based on Bayesian Shape Model. The BSM estimate the parameters of the model with an implementation of the EM algorithm. We describe the characterization methodology from parametric model and evaluated the accuracy for feature detection and estimation of the parameters associated with facial expressions, analyzing its robustness in pose and local variations. Then, a methodology for emotion characterization is introduced to perform the recognition. The experimental results show that the proposed model can effectively detect the different facial expressions. Outperforming conventional approaches for emotion recognition obtaining high performance results in the estimation of emotion present in a determined subject. The model used and characterizationmethodology showed efficient to detect the emotion type in 95.6% of the cases.
A novel approach for performance parameter estimation of face recognition bas...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.
A cloud based approach is proposed as a solution
for preventing accidents. The system provides face detection and
eye detection from the image captured using a low cost USB
camera. Then driver’s head pose is estimated using the region of
interest computed by Viola-Jones algorithm. The system also
contains a heart rate sensor for detecting the biological problems
of the driver and an alcohol sensor to detect whether the driver
has consumed alcohol or not. This combined system is used to
prevent drink and drive accident, accident due to inattention of
driver and accident due to driver’s biomedical problems.
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.
Face sketch synthesis via sparse representation based greedy searchjpstudcorner
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
Developing Scheduler Test Cases to Verify Scheduler Implementations In Time-T...ijesajournal
Despite that there is a “one-to-many” mapping between scheduling algorithms and scheduler implementations, only a few studies have discussed the challenges and consequences of translating between these two system models. There has been an argument that a wide gap exists between scheduling theory and scheduling implementation in practical systems, where such a gap must be bridged to obtain an effective validation of embedded systems. In this paper, we introduce a technique called “Scheduler Test Case” (STC) aimed at bridging the gap between scheduling algorithms and scheduler implementations in single-processor embedded systems implemented using Time-Triggered Co-operative (TTC) architectures. We will demonstrate how the STC technique can provide a simple and systematic way for documenting, verifying (testing) and comparing various TTC scheduler implementations on particular hardware. However, STC is a generic technique that provides a black-box tool for assessing and predicting the behaviour of representative implementation sets of any real-time scheduling algorithm.
Founded in 1998, Wevioo is an International Consulting Firm specialising in systems integration projects to support its clients in their performance improvement initiatives.
Une nouvelle logistique « Internet inside »ESCP Europe
Bernard Avril, Directeur Général, Dispeo (Groupe 3SI)
Nouveaux comportements consommateurs, quel impact sur la Supply Chain ?
7ème Forum d'été Supply Chain Magazine / ESCP Europe, 11 juillet 2013
Le Digital et le Supply chain, vers un nouveau paradigmeFabien Riou
Le digital intervient de plus en plus dans les supply chains des entreprises afin d'améliorer l'expérience consommateur. Le digital est vu comme un nouveau moteur.
AN EFFICIENT FEATURE EXTRACTION METHOD WITH LOCAL REGION ZERNIKE MOMENT FOR F...ieijjournal
Face recognition is one of the most challenging problems in the domain of image processing and machine vision. The face recognition system is critical when individuals have very similar biometric signature such as identical twins. In this paper, the facial area in an image is detected using AdaBoost approach. After that the facial area is divided into some local regions. Finally, new efficient facial-based identical twins feature extractor based on the geometric moment is applied into local regions of face image.The utilized geometric moment is Zernike Moment (ZM) as a feature extractor inside the local regions of facial area of identical twins images. The proposed method is evaluated on two datasets, Twins Days Festival and Iranian Twin Society which contain scaled and rotated facial images of identical twins in different illuminations. The results prove the ability of proposed method to recognize a pair of identical twins.Also, results show that the proposed method is robust to rotation, scaling and changing illumination.
WCTFR : W RAPPING C URVELET T RANSFORM B ASED F ACE R ECOGNITIONcsandit
The recognition of a person based on biological fea
tures are efficient compared with traditional
knowledge based recognition system. In this paper w
e propose Wrapping Curvelet Transform
based Face Recognition (WCTFR). The Wrapping Curve
let Transform (WCT) is applied on
face images of database and test images to derive c
oefficients. The obtained coefficient matrix is
rearranged to form WCT features of each image. The
test image WCT features are compared
with database images using Euclidean Distance (ED)
to compute Equal Error Rate (EER) and
True Success Rate (TSR). The proposed algorithm wit
h WCT performs better than Curvelet
Transform algorithms used in [1], [10] and [11].
This paper describes for a robust face recognition system using skin segmentation technique. This paper addresses the problem of detecting faces in color images in the presence of various lighting conditions. In this paper the face is preprocessed using histogram equalization to avoid illumination problems and then is detected using skin segmentation method. The principal component analysis using neural network is used to recognize the extracted facial features.
Facial landmarking localization for emotion recognition using bayesian shape ...csandit
This work presents a framework for emotion recognition, based in facial expression analysis
using Bayesian Shape Models (BSM) for facial landmarking localization. The Facial Action
Coding System (FACS) compliant facial feature tracking based on Bayesian Shape Model. The
BSM estimate the parameters of the model with an implementation of the EM algorithm. We
describe the characterization methodology from parametric model and evaluated the accuracy
for feature detection and estimation of the parameters associated with facial expressions,
analyzing its robustness in pose and local variations. Then, a methodology for emotion
characterization is introduced to perform the recognition. The experimental results show that
the proposed model can effectively detect the different facial expressions. Outperforming
conventional approaches for emotion recognition obtaining high performance results in the
estimation of emotion present in a determined subject. The model used and characterization
methodology showed efficient to detect the emotion type in 95.6% of the cases.
FACIAL LANDMARKING LOCALIZATION FOR EMOTION RECOGNITION USING BAYESIAN SHAPE ...cscpconf
This work presents a framework for emotion recognition, based in facial expression analysis using Bayesian Shape Models (BSM) for facial landmarking localization. The Facial Action Coding System (FACS) compliant facial feature tracking based on Bayesian Shape Model. The BSM estimate the parameters of the model with an implementation of the EM algorithm. We describe the characterization methodology from parametric model and evaluated the accuracy for feature detection and estimation of the parameters associated with facial expressions, analyzing its robustness in pose and local variations. Then, a methodology for emotion characterization is introduced to perform the recognition. The experimental results show that the proposed model can effectively detect the different facial expressions. Outperforming conventional approaches for emotion recognition obtaining high performance results in the estimation of emotion present in a determined subject. The model used and characterizationmethodology showed efficient to detect the emotion type in 95.6% of the cases.
A novel approach for performance parameter estimation of face recognition bas...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.
A cloud based approach is proposed as a solution
for preventing accidents. The system provides face detection and
eye detection from the image captured using a low cost USB
camera. Then driver’s head pose is estimated using the region of
interest computed by Viola-Jones algorithm. The system also
contains a heart rate sensor for detecting the biological problems
of the driver and an alcohol sensor to detect whether the driver
has consumed alcohol or not. This combined system is used to
prevent drink and drive accident, accident due to inattention of
driver and accident due to driver’s biomedical problems.
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.
Face sketch synthesis via sparse representation based greedy searchjpstudcorner
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
Developing Scheduler Test Cases to Verify Scheduler Implementations In Time-T...ijesajournal
Despite that there is a “one-to-many” mapping between scheduling algorithms and scheduler implementations, only a few studies have discussed the challenges and consequences of translating between these two system models. There has been an argument that a wide gap exists between scheduling theory and scheduling implementation in practical systems, where such a gap must be bridged to obtain an effective validation of embedded systems. In this paper, we introduce a technique called “Scheduler Test Case” (STC) aimed at bridging the gap between scheduling algorithms and scheduler implementations in single-processor embedded systems implemented using Time-Triggered Co-operative (TTC) architectures. We will demonstrate how the STC technique can provide a simple and systematic way for documenting, verifying (testing) and comparing various TTC scheduler implementations on particular hardware. However, STC is a generic technique that provides a black-box tool for assessing and predicting the behaviour of representative implementation sets of any real-time scheduling algorithm.
Founded in 1998, Wevioo is an International Consulting Firm specialising in systems integration projects to support its clients in their performance improvement initiatives.
Une nouvelle logistique « Internet inside »ESCP Europe
Bernard Avril, Directeur Général, Dispeo (Groupe 3SI)
Nouveaux comportements consommateurs, quel impact sur la Supply Chain ?
7ème Forum d'été Supply Chain Magazine / ESCP Europe, 11 juillet 2013
Le Digital et le Supply chain, vers un nouveau paradigmeFabien Riou
Le digital intervient de plus en plus dans les supply chains des entreprises afin d'améliorer l'expérience consommateur. Le digital est vu comme un nouveau moteur.
Volatility Forecasting - A Performance Measure of Garch Techniques With Diffe...ijscmcj
Volatility Forecasting is an interesting challengingtopicin current financial instruments as it is directly associated with profits. There are many risks and rewards directly associated with volatility. Hence forecasting volatility becomes most dispensable topic in finance. The GARCH distributionsplay an import ant role in the risk measurement a nd option pricing. T heminmotiveof this paper is tomeasure the performance of GARCH techniques for forecasting volatility by using different distribution model. We have used 9 variations in distribution models that are used to forecast t he volatility of a stock entity. Thedifferent GARCH
distribution models observed in this paper are Std, Norm, SNorm,GED, SSTD, SGED, NIG, GHYP and JSU.Volatility is forecasted for 10 days in dvance andvalues are compared with the actual values to find out the best distribution model for volatility forecast. From the results obtain it has been observed that GARCH withGED distribution models has outperformed all models
Facial expression identification by using features of salient facial landmarkseSAT Journals
Abstract
Facial expression recognition/identification (FER) systems plays vital role in the field of biometrics. Localizing the facial components accurately is a challenging task in image analysis and computer vision. Accurate detection of face and facial components gives effective performance with classification of expressions. This paper proposes feature based facial recognition system using JAFFE and CK databases. 18 facial landmarks were located using Haar cascade classifier. The distances between 12 points were extracted as features. These features were classified using SVM and K-NN classifier and comparison based on accuracy and execution time is done. The proposed algorithm gives better performance.
Facial expression identification by using features of salient facial landmarkseSAT Journals
Abstract
Facial expression recognition/identification (FER) systems plays vital role in the field of biometrics. Localizing the facial components accurately is a challenging task in image analysis and computer vision. Accurate detection of face and facial components gives effective performance with classification of expressions. This paper proposes feature based facial recognition system using JAFFE and CK databases. 18 facial landmarks were located using Haar cascade classifier. The distances between 12 points were extracted as features. These features were classified using SVM and K-NN classifier and comparison based on accuracy and execution time is done. The proposed algorithm gives better performance.
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).
Artículo presentado por la Universidad de Vigo durante la jornada HOIP'10 organizada por la Unidad de Sistemas de información e interacción de TECNALIA.
Más información en http://www.tecnalia.com/es/ict-european-software-institute/index.htm
FACIAL EXTRACTION AND LIP TRACKING USING FACIAL POINTSijcseit
Automatic facial feature extraction is one of the most important and attempted problems in computer
vision. It is a necessary step in face recognition, facial image compression. There are many methods have
been proposed in the literature for the facial feature extraction task. However, all of them have still
disadvantage such as not complete reflection about face structure, face texture. In this paper, we propose
a method for fast and accurate extraction of feature points such as eyes, nose, mouth, eyebrows and the
like from dynamic images with the purpose of face recognition. These methods are far from satisfactory
in terms of extraction accuracy and processing speed. The proposed method achieves high position
accuracy at a low computing cost by combining shape extraction with geometric features of facial images
like eyes, nose, mouth etc. In this paper, a facial expressions synthesis system, based on the facial points
tracking in the frontal image sequences. Selected facial points are automatically tracked using a crosscorrelation based optical flow. The proposed synthesis system uses a simple facial features model with a
few set of control points that can be tracked in original facial image sequences.
Effective driver distraction warning system incorporating fast image recognit...IJECEIAES
Modern cars are equipped with advanced automatic technology featuring various safety measures for car occupants. However, the growing density of vehicles, especially in areas where infrastructure development lags, poses potential dangers, particularly accidents caused by driver subjectivity. These incidents may occur due to driver distraction or the presence of high-risk obstacles on the road. This article presents a comprehensive solution to assist drivers in mitigating these risks. Firstly, the study introduces a novel method to enhance the recognition of a driver's facial features by analyzing benchmarks and the whites of the eyes to assess the distraction level. Secondly, a domain division method is proposed to identify obstacles and lanes in front of the vehicle, enabling the assessment of the danger level. This information is promptly relayed to the driver and relevant individuals, such as the driver's manager or supervisor. An experimental device has also been developed to evaluate the effectiveness of the algorithms, solutions, and processing capabilities of the system.
FACIAL EXPRESSION RECOGNITION USING DIGITALISED FACIAL FEATURES BASED ON ACTI...csandit
Facial Expression Recognition is a hot topic in recent years. As artificial intelligent technology is growing rapidly, to communicate with machines, facial expression recognition is essential.The recent feature extraction methods for facial expression recognition are similar to face
recognition, and those caused heavy load for calculation. In this paper, Digitalized Facial Features based on Active Shape Model method is used to reduce the computational complexity
and extract the most useful information from the facial image. The result shows by using this
method the computational complexity is dramatically reduced, and very good performance was obtained compared with other extraction methods.
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.
Driver Drowsiness is a grave issue resulting in many road accidents each year. To evaluate the exact number of sleep related accidents because of the difficulties in detecting whether fatigue was a factor and in assessing the level of fatigue is not currently possible. In this paper the camera will be placed besides the rare view mirror of car in way such that it is in clear view of the frontal face of the driver. This camera will continuously capture the video of driver’s frontal face while driving. The system will detect the frontal face in the image and later the eyes. Depending upon the conditions the system will generate an alert. The focus will be on the system that will accurately monitor the open or closed state of the driver’s eyes in real-time. By monitoring the eyes, it is believed that the symptoms of driver fatigue can be detected early to avoid accidents.
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vision. The face recognition system is critical when individuals have very similar biometric signature such
as identical twins. In this paper, new efficient facial-based identical twins recognition is proposed
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Twin Society which contain scaled and rotated facial images of identical twins in different illuminations.
The results prove the ability of proposed method to recognize a pair of identical twins. Also, results show
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Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
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Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
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1. International Journal of Soft Computing, Mathematics and Control (IJSCMC), Vol. 5, No. 1, February 2016
DOI: 10.14810/ijscmc.2016.5101 1
AN ALGORITHM TO DETECT DRIVER’S
DROWSINESS BASED ON NODDING BEHAVIOUR
Lam Thanh Hien1
, and Do Nang Toan2
1
Lac Hong University, Dong Nai, Vietnam
2
Vietnam National University, Ha Noi, Vietnam
ABSTRACT
Driver’s drowsiness is one of the major causes of serious accidents in road traffic. Thus, special effort in
searching for better assistant technology has been paid. However, several existing approaches fail to work
effectively as the head of a drowsy driver is usually in slanting state. Moreover, the shaking of vehicle or
the driver’s winking even makes the problem much more complicated. Anyway, head bend posture also
signifies a drowsy state. Consequently, this paper proposes a novel approach by considering head nodding
behaviour as an input in our detection model. After detecting a human face, some significant facial features
are extracted; then, they are used to calculate the predetermined optimal parameters; finally, drowsiness is
evaluated based on these thresholds. In our empirical experiments, the proposed algorithm can successfully
and accurately detect 96.56% of cases.
KEYWORDS
Driver drowsiness, Algorithm, Nodding behaviour, Facial Normal
1. INTRODUCTION
Driver’s drowsiness is one of the major causes of serious accidents in road traffic. It usually
occurs when a driver fails to have enough sleep or enough rest for/after a long trip, leading to a
decrease in his/her observation and reaction ability. As a matter of fact, after sitting still for a long
time, the vibration, noise, and shaking make drivers tired; and if he/she tries to continue the trip
without taking a proper rest, he/she may easily fall into drowsiness which results in distraction
and unconscious state; hence, he/she naturally loses his/her control of the vehicle awhile. A few
seconds of unconsciously losing the control may cause a disaster because the driver fails to have
enough time to reflex to avoid obstacles and/or other vehicles.
The above problem has attracted special attention of researchers in searching for optimal models
to detect and alert driver’s drowsiness. Grace et al. [1] established a non-parameter neural
network model to estimate the level of PERCLOS in monitoring and detecting the sleepy state of
heavy-truck drivers. Vural et al. [2] used Adaboost and multiple regression approach to classify
30 behavioural faces based on FACS system as shown in Figure 1; and they achieved a successful
result of more than 90%. Lin et al. [3] proposed a wireless real-time electroencephalogram (EEG)
system based on brain-computer interface (BCI) to detect drowsiness while Liu et al. [4]
suggested an algorithm based on the movement principles of eyelashes with an acceptable
efficiency.
One of the key characteristics of a drowsy person is the head bend posture, which leads us to a
more difficult problem - detecting driver’s drowsiness in slanting state, i.e. driver face is not in-
line with the equipped camera. Moreover, the shaking of vehicle or the driver’s winking even
2. International Journal of Soft Computing, Mathematics and Control (IJSCMC), Vol. 5, No. 1, February 2016
2
makes the problem much more complicated. However, head bend posture also signifies a drowsy
state. Thus, this paper proposes a novel approach by considering head nodding behaviour as an
input in our detection model. Some key parameters presenting head nodding behaviour will be
optimized before conducting further steps. Specifically, after detecting a human face, some
significant facial features are extracted; then, they are used to calculate the predetermined optimal
parameters; finally, drowsiness is evaluated based on these thresholds.
Figure 1. Detection system proposed by Vural et al. [2]
The rest of this paper is organized as the following: related studies are summarized in Section 2
while Section 3 presents our proposed approach. Our experiments and results are discussed in
Section 4; and some concluding remarks make up the last section.
2. RELATED STUDIES
2.1. ACTIVE APPEARANCE MODEL (AAM)
Active Appearance Model (AAM) proposed by Cootes et al. [5] is actually an algorithm to detect
key facial features which carries specific and different characteristics. In AAM, a statistical model
respective to the appearance of an object in image is used to combine with an optimal algorithm
to determine appropriate parameters in displaying respective image model. However, their
approach is built on a quite complicated mapping function and depends on the size of the dataset.
Hence, with a modification of AAM, Baker & Matthews [6] found that their proposed model
provides better results and real-time convergence in some specific usage cases. Or Xiao et al. [7]
further modified the AAM model by incorporating 2D and 3D information.
Figure 2: Shape and image structure in AAM
3. International Journal of Soft Computing, Mathematics and Control (IJSCMC), Vol. 5, No. 1, February 2016
3
In AAM, object of interest is modelled with a set of shape description features and its image
structure as shown in Figure 2, which is actually the sample of image intensity in certain regions
constrained by a control set. A statistical model of the object can effectively describe its shape
variations, its image structure variations as well as correlation among them. Prominent issues
concerned in this approach include establishing a statistical model for image object and designing
an optimal searching algorithm. It should be noted that the establishing of a statistical model for
an object includes a model for its shape and another one for its structure. Combining these two
models results in a certain model for the whole object.
2.2. FACIAL NORMAL MODEL
Gee & Cipolla (1994) proposed the facial normal model with five facial features, including two
far corners of eyes, two points of mouth corners, and the tip of nose, among which the four points
of eyes and mouth corners make up a plane called facial plane denoted by Oxy. In 3D space,
facial normal can be easily achieved by having the normal of facial plane Oxy at the nose tip as
shown in Figure 3 [8,9]. Figure 3 demonstrates a coordinate system Oxyz which is assumed to be
located at the center of the camera. The horizontal and vertical directions in the image are
respectively denoted by Ox and Oy axes while the normal to the image plane is presented by Oz.
Figure 3. Facial Normal Model
The symmetric axis of the facial plane should be first determined by joining the midpoints of the
two points of far corners of eyes and two points of far corners of mouth. Then, we need to provide
two predetermined ratios, namely as m m fR L L and n n fR L L where Lm, Ln, and Lf are
accordingly measured as plotted in Figure 4. From these facts, we can accordingly estimate the
direction of facial normal in 3D space.
Figure 4. Fundamental parameters Lm, Ln, and Lf
4. International Journal of Soft Computing, Mathematics and Control (IJSCMC), Vol. 5, No. 1, February 2016
4
Because length ratios along the symmetric axis are preserved, we can easily locate the nose base
along the axis by using the model ratio Rm. Then, we join the nose base and the nose tip to
determine the facial normal in the image. Consequently, the angle between the facial normal in
the image and the Ox axis is used to define tilt direction of the normal whereas the slant angle
between the optical axis and the facial normal in 3D space is also used to establish the normal.
Basically, we can obtain the slant angle from the model ratio Rn [8]. Thus, in the coordinate
system Oxyz, the facial normal ˆn is determined by
ˆ sin cos ,sin sin , cos .n
3. DETECTION OF NODDING BEHAVIOUR
3.1. SELECTION OF SHAPE PARAMETERS
There have been several approaches proposing shape parameters which can be constructed based
on face-operated model, anthropology features, ratio of body parts, colour and types of shapes of
each part; for example, willow-leaf eyebrows are usually long, tapering at the tail, round-tapering
at the head, thick and bright like curved leaves. In fact, searching for these features to construct an
appropriate model takes a lot of time and effort. Hence, to overcome this issue, in the problem of
detecting driver’s drowsiness, this paper does not require the shape features of each part but the
correlation among some key characteristics presenting different attributes of nodding behaviour.
Base on a control set extracted from driver’s face, we construct some fundamental parameters
directly computed from the set. In practice, there are several computational methods; however,
this paper works with some parameters, such as point-point distance, point-edge distance, the area
of triangular constrained by two points of mouth corners and tip nose due to their easy
computation and differentiated ability.
This paper uses an image database of faces that are marked with set of points and labeled with
either head-up or head-down tags. With each feature, we count respective values of the selected
parameters in the database and find detaching thresholds so that the problem can be transformed
into equivalent problem of constructing one-level decision tree and evaluating errors. Some
features with high detachment ability are selected to determine whether head is bent down. As
such, our proposed algorithm automatically extracts control set of points with the AAM. From the
set, some control points that can serve the estimate head direction are then selected to become
inputs of the facial normal model to compute shape parameters.
3.2. AN ALGORITHM TO DETECT NODDING HEAD FROM CAMERA
From the above reviews, the following procedure is suggested to detect nodding behaviour:
Input: Frame flows from camera or video;
Output: Head state (Normal, Nodding);
@ Some basic denotations:
N: Nose point;
E1: Left eye corner;
E2: Right eye corner;
M1: Mouth left corner;
M2: Mouth right corner;
H: Point in M1M2 line (NHM1M2);
dm: distance from N to H;
s3: area of NM1M2;
5. International Journal of Soft Computing, Mathematics and Control (IJSCMC), Vol. 5, No. 1, February 2016
5
@ Basic steps:
- Create initial values of:
std_dm;
std_s3;
std_brect(bounding rectangle);
status := HEAD_NORMAL;
thres1;
thres2;
thres3;
thres4;
- For each frame:
calculate cur_dm, cur_s3, cur_brect;
x := (std_brect.x-cur_brect.x)/std_brect.width;
y := (std_brect.y-cur_brect.y)/std_brect.width;
if (y thres1 AND < thres2)
if (status=HEAD_NOD) return;
else if (std_dm/cur_dm thres3 AND std_s3/cur_s3>thres4) status:= HEAD_NOD;
else status:=HEAD_NORMAL;
4. EMPIRICAL EXPERIMENTS
This paper tests the proposed algorithm with two types of data, including: (1) virtual images
created from 3D model with several reference parameters that are already determined from
defined transformation model and the model is then rotated with different angles and aspects to
test the performance of the algorithm; and (2) real images obtained from camera and video. The
data are classified so that they can be used in the learning phase of selected parameters with
respective evaluation thresholds and in detecting phase as well. Particularly, besides the 3D
images, we conducted experiments with 11 videos of 11 different people recorded at Duy Tan
University (Da Nang City, Vietnam) at the rate of 15 frames/second and image resolution of
640x480.
In order to assist the process of selecting appropriate parameters, we organize a database of 5,836
pieces of marked images created from 3D model as shown in Figure 5 and real images extracted
from camera. This set is used to compute the values of several parameters so that we can select
optimal ones. Our experimental results indicate that we can obtain optimal values of concerned
parameters as shown in Figure 6 and Figure 7.
Moreover, from the above database, we select out a set of 2,530 images to test the performance of
our proposed algorithm in detecting nodding behaviour. It shows that our algorithm can
successfully and accurately detect 96.56% of cases as shown in Figure 8. Some cases can’t be
correctly detected due to the failure of detecting the set of feature points as shown in Figure 9.
6. International Journal of Soft Computing, Mathematics and Control (IJSCMC), Vol. 5, No. 1, February 2016
6
Figure 5.3D virtual image
Figure 6. Distribution of parameter dm
Figure 7. Distribution of another parameter
Figure 8. Samples of correct detection of feature points
7. International Journal of Soft Computing, Mathematics and Control (IJSCMC), Vol. 5, No. 1, February 2016
7
Figure 9. Samples of incorrect detection of feature points
Besides, in order to develop an integrative system to monitor driver’s drowsiness, a
computational program with the proposed algorithm is tested for its ability of detecting nodding
behaviour to alert driver. The testing program is written based on Visual C++2008 with the
support from the open source library OpenCV. The inputs for the program are from video or
webcam. The program then automatically determine key feature points of the faces by analysing
their parts and monitor face declination; when it detects nodding actions, the system alarms on its
monitor.
Empirical study shows that the program works at real-time speed and gives high ratio of accurate
results in the specified testing environment as shown in Figure 10. However, there are still some
cases that the program fails to correctly perform its task because key facial feature points are not
accurately detected.
Figure 10. Screen shots of our testing program
5. CONCLUSION
Human head in digital image has been an interesting research topic; and several practical
applications have been developed from such studies in identifying faces, monitoring human
activities, human-machine interaction, and there are still many issues left unsolved. This paper
proposes a novel approach in determining nodding behaviour based on optimal selection criteria
for some parameters of shape features. Next research would focus on combining some techniques
to better detect key facial feature points and integrate into driver monitoring system to improve
traffic safety.
REFERENCES
[1] Grace R., Byrne V.E., Bierman D.M., Legrand J.M., Gricourt D., Davis B.K., Staszewski J.J.,
Carnahan B. (1998), “A drowsy driver detection system for heavy vehicles”, Digital Avionics
Systems Conference Proceedings, Vol. 2, I36/1 - I36/8.
[2] Vural E., Cetin M., Ercil A., Littlewort G., Bartlett M., Movellan J. (2007), “Drowsy Driver Detection
through Facial Movement Analysis”, Human–Computer Interaction, Vol. 4796 of LNCS, 6-18.
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[3] Lin C.T., Chang C.J., Lin B.S., Hung S.H., Chao C.F., Wang I.J. (2010), “A Real-Time Wireless
Brain–Computer Interface System for Drowsiness Detection”, IEEE Transactions on Biomedical
Circuits and Systems, Vol. 4, No. 4, 214-222.
[4] Liu D., Sun P., Xiao Y.Q., Yin Y. (2010), “Drowsiness Detection Based on Eyelid Movement”,
Second International Workshop on Education Technology and Computer Science, Vol. 2, 49 – 52.
[5] Cootes T.F., Edwards G.J., Taylor C.J. (1998), “Active appearance models”, In H.Burkhardt and B.
Neumann, editors, 5th European Conference on Computer Vision, Vol. 2, 484-498.
[6] Baker S., Matthews I. (2001), “Equivalence and efficiency of image alignment algorithms”, Computer
Vision and Pattern Recognition Conference 2001, Vol. 1, 1090-1097.
[7] Xiao J., Baker S., Matthews I., Kanade T. (2004), “Real-Time Combined 2D+3D Active Appearance
Models”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 535 -
542.
[8] Gee A., Cipolla R. (1994), “Determining the Gaze of Faces in Images”, Image and Vision Computing,
Vol. 12, No. 10, 639-647.
[9] Hien L.T., Toan D.N., Lang T.V. (2015), “Detection of Human Head Direction Based on Facial
Normal Algorithm”, International Journal of Electronics Communication and Computer Engineering,
Vol. 6, No. 1, 110-114.
AUTHORS
Lam Thanh Hien received his MSc. Degree in Applied Informatics Technology in 2004
from INNOTECH Institute, France. He is currently working as a Vice-Rector of Lac Hong
University. His main research interests are Information System and Image Processing.
Do Nang Toan is an Associate professor in Computer Science of Vietnam National
University. He received BSc. Degree in Applied Mathematics and Informatics in 1990 from
Hanoi University and PhD in Computer Science in 2001 from Vietnam Academy of Science
and Technology. He is currently work ing as a Head of Department of Virtual reality
technology at Institute of Information Technology, Vietnamese Academy of Science and
Technology and as Dean of Faculty of Multimedia Communications, Thai Nguyen
University of Information and Communication Technology. His main research interests are Pattern
recognition, Image processing and Virtual reality.