: 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.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
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.
Abstract: This paper presents a new face parts information analyzer, as a promising model for detecting faces and locating the facial features in images. The main objective is to build fully automated human facial measurements systems from images with complex backgrounds. Detection of facial features such as eye, nose, and mouth is an important step for many subsequent facial image analysis tasks. The main study of face detection is detect the portion of part and mention the circle or rectangular of the every portion of body. In this paper face detection is depend upon the face pattern which is match the face from the pattern reorganization. The study present a novel and simple model approach based on a mixture of techniques and algorithms in a shared pool based on viola jones object detection framework algorithm combined with geometric and symmetric information of the face parts from the image in a smart algorithm.Keywords: Face detection, Video frames, Viola-Jones, Skin detection, Skin color classification, Face reorganization, Pattern reorganization. Skin Color.
Title: Face Detection Using Modified Viola Jones Algorithm
Author: Alpika Gupta, Dr. Rajdev Tiwari
International Journal of Recent Research in Mathematics Computer Science and Information Technology
ISSN 2350-1022
Paper Publications
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
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.
Abstract: This paper presents a new face parts information analyzer, as a promising model for detecting faces and locating the facial features in images. The main objective is to build fully automated human facial measurements systems from images with complex backgrounds. Detection of facial features such as eye, nose, and mouth is an important step for many subsequent facial image analysis tasks. The main study of face detection is detect the portion of part and mention the circle or rectangular of the every portion of body. In this paper face detection is depend upon the face pattern which is match the face from the pattern reorganization. The study present a novel and simple model approach based on a mixture of techniques and algorithms in a shared pool based on viola jones object detection framework algorithm combined with geometric and symmetric information of the face parts from the image in a smart algorithm.Keywords: Face detection, Video frames, Viola-Jones, Skin detection, Skin color classification, Face reorganization, Pattern reorganization. Skin Color.
Title: Face Detection Using Modified Viola Jones Algorithm
Author: Alpika Gupta, Dr. Rajdev Tiwari
International Journal of Recent Research in Mathematics Computer Science and Information Technology
ISSN 2350-1022
Paper Publications
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.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
International Journal of Engineering Research and Development is an international premier peer reviewed open access engineering and technology journal promoting the discovery, innovation, advancement and dissemination of basic and transitional knowledge in engineering, technology and related disciplines.
Abstract: Face Recognition appears to be an integral part in human-computer interfaces and eservices. To carry out security and fault tolerance various Image Processing techniques have been incorporated using ‘Curse of Dimensionality’ that refers to Classifying a pattern with high dimensions that requires a large number of training data. A face recognition & Detection system is a computer-driven application for automatically identifying or verifying a person from still or video image. It does that by comparing selected facial features in the live image and a facial database where the system returns a possible list of faces corresponding to training samples from the database. The nodal points are measured creating a numerical code, called a faceprint, representing the face in the database. Relatively many techniques are used. Image processing technique has been implemented using Feature extraction by Gabor Filters and database training data using Neural Networks. Multiscale resolution and matrix sampling is efficiently performed using this technique.
Keywords: Image Processing techniques, Curse of Dimensionality, Faceprint, Feature extraction, Gabor Filters, Neural Networks.
Deep learning based facial expressions recognition system for assisting visua...journalBEEI
In general, a good interaction including communication can be achieved when verbal and non-verbal information such as body movements, gestures, facial expressions, can be processed in two directions between the speaker and listener. Especially the facial expression is one of the indicators of the inner state of the speaker and/or the listener during the communication. Therefore, recognizing the facial expressions is necessary and becomes the important ability in communication. Such ability will be a challenge for the visually impaired persons. This fact motivated us to develop a facial recognition system. Our system is based on deep learning algorithm. We implemented the proposed system on a wearable device which enables the visually impaired persons to recognize facial expressions during the communication. We have conducted several experiments involving the visually impaired persons to validate our proposed system and the promising results were achieved.
Age Invariant Face Recognition using Convolutional Neural Network IJECEIAES
In the recent years, face recognition across aging has become very popular and challenging task in the area of face recognition. Many researchers have contributed in this area, but still there is a significant gap to fill in. Selection of feature extraction and classification algorithms plays an important role in this area. Deep Learning with Convolutional Neural Networks provides us a combination of feature extraction and classification in a single structure. In this paper, we have presented a novel idea of 7-Layer CNN architecture for solving the problem of aging for recognizing facial images across aging. We have done extensive experimentations to test the performance of the proposed system using two standard datasets FGNET and MORPH (Album II). Rank-1 recognition accuracy of our proposed system is 76.6% on FGNET and 92.5% on MORPH (Album II). Experimental results show the significant improvement over available state-of- the-arts with the proposed CNN architecture and the classifier.
Real Time Facial Expression Recognition and Imitationijtsrd
The object of this paper was Real Time Facial Expression Recognition FER has become main area of interest due to its wide applications. Automatic Facial expression recognition has drawn the attention of researchers as it has many applications. Facial Expression Recognition gives important information about emotions of a human being. Many feature selection methods have been developed for identification of expressions from still images and real time videos. This work gives a detailed review of research works done in the field of facial expression identification and various methodologies implemented for facial expression recognition. Varsha Kushwah | Madhuri Diwakar | Tej Kumar | Dushyant Singh "Real Time Facial Expression Recognition and Imitation" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31584.pdf Paper Url :https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/31584/real-time-facial-expression-recognition-and-imitation/varsha-kushwah
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.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
International Journal of Engineering Research and Development is an international premier peer reviewed open access engineering and technology journal promoting the discovery, innovation, advancement and dissemination of basic and transitional knowledge in engineering, technology and related disciplines.
Abstract: Face Recognition appears to be an integral part in human-computer interfaces and eservices. To carry out security and fault tolerance various Image Processing techniques have been incorporated using ‘Curse of Dimensionality’ that refers to Classifying a pattern with high dimensions that requires a large number of training data. A face recognition & Detection system is a computer-driven application for automatically identifying or verifying a person from still or video image. It does that by comparing selected facial features in the live image and a facial database where the system returns a possible list of faces corresponding to training samples from the database. The nodal points are measured creating a numerical code, called a faceprint, representing the face in the database. Relatively many techniques are used. Image processing technique has been implemented using Feature extraction by Gabor Filters and database training data using Neural Networks. Multiscale resolution and matrix sampling is efficiently performed using this technique.
Keywords: Image Processing techniques, Curse of Dimensionality, Faceprint, Feature extraction, Gabor Filters, Neural Networks.
Deep learning based facial expressions recognition system for assisting visua...journalBEEI
In general, a good interaction including communication can be achieved when verbal and non-verbal information such as body movements, gestures, facial expressions, can be processed in two directions between the speaker and listener. Especially the facial expression is one of the indicators of the inner state of the speaker and/or the listener during the communication. Therefore, recognizing the facial expressions is necessary and becomes the important ability in communication. Such ability will be a challenge for the visually impaired persons. This fact motivated us to develop a facial recognition system. Our system is based on deep learning algorithm. We implemented the proposed system on a wearable device which enables the visually impaired persons to recognize facial expressions during the communication. We have conducted several experiments involving the visually impaired persons to validate our proposed system and the promising results were achieved.
Age Invariant Face Recognition using Convolutional Neural Network IJECEIAES
In the recent years, face recognition across aging has become very popular and challenging task in the area of face recognition. Many researchers have contributed in this area, but still there is a significant gap to fill in. Selection of feature extraction and classification algorithms plays an important role in this area. Deep Learning with Convolutional Neural Networks provides us a combination of feature extraction and classification in a single structure. In this paper, we have presented a novel idea of 7-Layer CNN architecture for solving the problem of aging for recognizing facial images across aging. We have done extensive experimentations to test the performance of the proposed system using two standard datasets FGNET and MORPH (Album II). Rank-1 recognition accuracy of our proposed system is 76.6% on FGNET and 92.5% on MORPH (Album II). Experimental results show the significant improvement over available state-of- the-arts with the proposed CNN architecture and the classifier.
Real Time Facial Expression Recognition and Imitationijtsrd
The object of this paper was Real Time Facial Expression Recognition FER has become main area of interest due to its wide applications. Automatic Facial expression recognition has drawn the attention of researchers as it has many applications. Facial Expression Recognition gives important information about emotions of a human being. Many feature selection methods have been developed for identification of expressions from still images and real time videos. This work gives a detailed review of research works done in the field of facial expression identification and various methodologies implemented for facial expression recognition. Varsha Kushwah | Madhuri Diwakar | Tej Kumar | Dushyant Singh "Real Time Facial Expression Recognition and Imitation" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31584.pdf Paper Url :https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/31584/real-time-facial-expression-recognition-and-imitation/varsha-kushwah
Face detection is one of the most suitable applications for image processing and biometric programs. Artificial neural networks have been used in the many field like image processing, pattern recognition, sales forecasting, customer research and data validation. Face detection and recognition have become one of the most popular biometric techniques over the past few years. There is a lack of research literature that provides an overview of studies and research-related research of Artificial neural networks face detection. Therefore, this study includes a review of facial recognition studies as well systems based on various Artificial neural networks methods and algorithms.
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.
Facial emoji recognition is a human computer interaction system. In recent times, automatic face recognition or facial expression recognition has attracted increasing attention from researchers in psychology, computer science, linguistics, neuroscience, and similar fields. Facial emoji recognizer is an end user application which detects the expression of the person in the video being captured by the camera. The smiley relevant to the expression of the person in the video is shown on the screen which changes with the change in the expressions. Facial expressions are important in human communication and interactions. Also, they are used as an important tool in studies about behavior and in medical fields. Facial emoji recognizer provides a fast and practical approach for non meddlesome emotion detection. The purpose was to develop an intelligent system for facial based expression classification using CNN algorithm. Haar classifier is used for face detection and CNN algorithm is utilized for the expression detection and giving the emoticon relevant to the expression as the output. N. Swapna Goud | K. Revanth Reddy | G. Alekhya | G. S. Sucheta ""Facial Emoji 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/ijtsrd23166.pdf
Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/23166/facial-emoji-recognition/n-swapna-goud
Emotion plays an important role in daily life of human being. The need and importance of automatic emotion recognition has grown with increasing role of human computer interaction applications. All emotion is derived from the presence of stimulus in body which evoke the physiological response. Yash Bardhan | Tejas A. Fulzele | Prabhat Ranjan | Shekhar Upadhyay | Prof. V.D. Bharate"Emotion Recognition using Image Processing" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: http://www.ijtsrd.com/papers/ijtsrd10995.pdf http://www.ijtsrd.com/engineering/telecommunications/10995/emotion-recognition-using-image-processing/yash-bardhan
The goal of this paper is to present a critical survey of existing literatures on human face detection and recognition over the last 4-5 years. An application for automatic face detection and tracking in video streams from surveillance cameras in public or commercial places is discussed in this paper. Prototype is designed to work with web cameras for the face detection and tracking system based on Visual 2010 C# and Open CV. This system can be used for security purpose to record the visitor face as well as to detect and track the face.
Keywords:- Face Detection, Face Recognition, Open CV, Face Tracking, Video Streams.
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.
Real Time Facial Emotion Recognition using Kinect V2 Sensoriosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Understanding the Impact and Challenges of Corona Crisis on Education Sector...vivatechijri
n the second week of March 2020, governments of all states in a country suddenly declared
shutting down of all colleges and schools for a temporary period of time as an immediate measure to stop the
spread of pandemic that is of novel corona virus. As the days pass by almost close to a month with no certainty
when they will again reopen. Due to pandemic like this an alarm bells have started sounding in the field of
education where a huge impact can be seen on teaching and learning process as well as on the entire education
sector in turn. The pandemic disruption like this is actually gave time to educators of today to really think about
the sector. Through the present research article, the author is highlighting on the possible impact of
coronavirus on education sector with the future challenges for education sector with possible suggestions.
LEADERSHIP ONLY CAN LEAD THE ORGANIZATION TOWARDS IMPROVEMENT AND DEVELOPMENT vivatechijri
This paper is explaining that how only leadership is responsible for sustainable improvement and
growth and only it can lead the organization towards improvement and overall development. Leadership and its
effectiveness are discussed in this research work and also how leadership is a different way of the success of the
organization and different from the traditional management to create true work-culture and good-will of the
organization in the social scene. Leadership is only responsible in bringing positive and negative change in the
organization; if the leadership doesn’t have the concern in the organization, the organization will not be able to
lead in the right direction towards improvement and development.
The topic of assignment is a critical problem in mathematics and is further explored in the real
physical world. We try to implement a replacement method during this paper to solve assignment problems with
algorithm and solution steps. By using new method and computing by existing two methods, we analyse a
numerical example, also we compare the optimal solutions between this new method and two current methods. A
standardized technique, simple to use to solve assignment problems, may be the proposed method
Structural and Morphological Studies of Nano Composite Polymer Gel Electroly...vivatechijri
n today’s society, we stand before a change in energy scarcity. As our civilization grows, many
countries in thedeveloping world seek to have the standard of living that has been exclusive to a few nations, so
their arises a need in thedevelopment of technology that is compatible enough with the resources provided by
nature in order to have sustainabledevelopment to all class of the society. In order to overcomethe prevailing
challenges of huge energy crises in near future, there is an urgent need for the development of electrical
vehiclesor hybrid electrical vehicles with low CO2 emissions using renewable energy sources. In view of the
above, electrochemicalcapacitors can fulfil the requirements to some extent.Preparation of nano composite
polymer gel electrolyte is the best optional product to overcome these problems. When fillers are added or
dispersed to the polymer gel electrolyte, amorphous or porous nature of electrolyte increases which enhances
the liquid absorbing quality of polymer and helps in removing the drawbacks of polymer gel electrolytes such as
leakage, poor mechanical and thermal stability etc. In this work dispersion of SiO2 nano filler is done in the
[PVdF (HFP)-PC-Mg (ClO4)2] for the synthesis of nano composite PGE [PVdF (HFP)-PC-MgClO4- SiO2].
Optimization and characterization was carried out by using various techniques.
Theoretical study of two dimensional Nano sheet for gas sensing applicationvivatechijri
This study is focus on various two dimensional material for sensing various gases with theoretical
view for new research in gas sensing application. In this paper we review various two dimensional sheet such as
Graphene, Boron Nitride nanosheet, Mxene and their application in sensing various gases present in the
atmosphere.
METHODS FOR DETECTION OF COMMON ADULTERANTS IN FOODvivatechijri
Food is essential forliving. Food adulteration deceives consumers and can endanger their health. The
purpose of this document is to list common food adulterant methods commonly found in India. An adulterant is
a substance found in other substances such as food, cosmetics, pharmaceuticals, fuels, or other chemicals that
compromise the safety or effectiveness of that substance. The addition of adulterants is called adulteration. The
most common reason for adulteration is the use of undeclared materials by manufacturers that are cheaper than
the correct and declared ones. The adulterants can be harmful or reduce the effectiveness of the product, or
they can be harmless.
The novel ideas of being a entrepreneur is a key for everyone to get in the hustle, but developing a
idea from core requires a systematic plan, time management, time investment and most importantly client
attention. The Time required for developing may vary from idea to idea and strength of the team. Leadership to
build a team and manage the same throughout the peak of development is the main quality. Innovations and
Techniques to qualify the huddles is another aspect of Business Development and client Retention.
Innovation for supporting prosperity has for quite some time been a focus on numerous orders, including PC science, brain research, and human-PC connection. In any case, the meaning of prosperity isn't continuously clear and this has suggestions for how we plan for and evaluate advances that intend to cultivate it. Here, we talk about current meanings of prosperity and how it relates with and now and then is a result of self-amazing quality. We at that point center around how innovations can uphold prosperity through encounters of self-amazing quality, finishing with conceivable future bearings.
An Alternative to Hard Drives in the Coming Future:DNA-BASED DATA STORAGEvivatechijri
Demand for data storage is growing exponentially, but the capacity of existing storage media is not keeping up, there emerges a requirement for a storage medium with high capacity, high storage density, and possibility to face up to extreme environmental conditions. According to a research in 2018, every minute Google conducted 3.88 million searches, other people posted 49,000 photos on Instagram, sent 159,362,760 e-mails, tweeted 473,000 times and watched 4.33 million videos on YouTube. In 2020 it estimated a creation of 1.7 megabytes of knowledge per second per person globally, which translates to about 418 zettabytes during a single year. The magnetic or optical data-storage systems that currently hold this volume of 0s and 1s typically cannot last for quite a century. Running data centres takes vast amounts of energy. In short, we are close to have a substantial data-storage problem which will only become more severe over time. Deoxyribonucleic acid (DNA) are often potentially used for these purposes because it isn't much different from the traditional method utilized in a computer. DNA’s information density is notable, 215 petabytes or 215 million gigabytes of data can be stored in just one gram of DNA. First we can encode all data at a molecular level and then store it in a medium that will last for a while and not become out-dated just like floppy disks. Due to the improved techniques for reading and writing DNA, a rapid increase is observed in the amount of possible data storage in DNA.
The usage of chatbots has increased tremendously since past few years. A conversational interface is an interface that the user can interact with by means of a conversation. The conversation can occur by speech but also by text input. When a chatty interface uses text, it is also described as a chatbot or a conversational medium. During this study, the user experience factors of these so called chatbots were investigated. The prime objective is “to spot the state of the art in chatbot usability and applied human-computer interaction methodologies, to research the way to assess chatbots usability". Two sorts of chatbots are formulated, one with and one without personalisation factors. the planning of this research may be a two-by-two factorial design. The independent variables are the two chatbots (unpersonalised versus personalised) and thus the speci?c task or goal the user are ready to do with the chatbot within the ?nancial ?eld (a simple versus a posh task). The results are that there was no noteworthy interaction effect between personalisation and task on the user experience of chatbots. A signi?cant di?erence was found between the two tasks with regard to the user experience of chatbots, however this variation wasn't because of personalisation.
The Smart glasses Technology of wearable computing aims to identify the computing devices into today’s world.(SGT) are wearable Computer glasses that is used to add the information alongside or what the wearer sees. They are also able to change their optical properties at runtime.(SGT) is used to be one of the modern computing devices that amalgamate the humans and machines with the help of information and communication technology. Smart glasses is mainly made up of an optical head-mounted display or embedded wireless glasses with transparent heads- up display or augmented reality (AR) overlay in it. In recent years, it is been used in the medical and gaming applications, and also in the education sector. This report basically focuses on smart glasses, one of the categories of wearable computing which is very popular presently in the media and expected to be a big market in the next coming years. It Evaluate the differences from smart glasses to other smart devices. It introduces many possible different applications from the different companies for the different types of audience and gives an overview of the different smart glasses which are available presently and will be available after the next few years.
Future Applications of Smart Iot Devicesvivatechijri
With the Internet of Things (IoT) bit by bit creating as the resulting time of the headway of the Internet, it gets critical to see the diverse expected zones for the utilization of IoT and the research challenges that are connected with these applications going from splendid savvy urban areas, to medical care administrations, shrewd farming, collaborations and retail. IoT is needed to attack into for all expectations and purposes for all pieces of our day-to-day life. Despite the fact that the current IoT enabling advancements have immensely improved in the continuous years, there are so far different issues that require attention. Since the IoT ideas results from heterogeneous advancements, many examination difficulties will arise. In like manner, IoT is planning for new components of exploration to be finished. This paper presents the progressing headway of IoT advancements and inspects future applications.
Cross Platform Development Using Fluttervivatechijri
Today the development of cross-platform mobile application has under the state of compromise. The developers are not willing to choose an alternative of either building the similar app many times for many operating systems or to accept a lowest common denominator and optimal solution that will going to trade the native speed, accuracy for portability. The Flutter is an open-source SDK for creating high-performance, high fidelity mobile apps for the development of iOS and Android. Few significant features of flutter are - Just-in-time compilation (JIT), Ahead- of-time compilation (AOT compilation) into a native (system-dependent) machine code so that the resulting binary file can execute natively. The Flutter’s hot reload functionality helps us to understand quickly and easily experiment, build UIs, add features, and fix bugs. Hot reload works by injecting updated source code files into the running Dart Virtual Machine (VM). With the help of Flutter, we believe that we would be having a solution that gives us the best of both worlds: hardware accelerated graphics and UI, powered by native ARM code, targeting both popular mobile operating systems.
The Internet, today, has become an important part of our lives. The World Wide Web that was once a small and inaccessible data storage service is now large and valuable. Current activities partially or completely integrated into the physical world can be made to a higher standard. All activities related to our daily life are mapped and linked to another business in the digital world. The world has seen great strides in the Internet and in 3D stereoscopic displays. The time has come to unite the two to bring a new level of experience to the users. 3D Internet is a concept that is yet to be used and requires browsers to be equipped with in-depth visualization and artificial intelligence. When this material is included, the Internet concept of material may become a reality discussed in this paper. In this paper we have discussed the features, possible setting methods, applications, and advantages and disadvantages of using the Internet. With this paper we aim to provide a clear view of 3D Internet and the potential benefits associated with this obviously cost the amount of investment needed to be used.
Recommender System (RS) has emerged as a significant research interest that aims to assist users to seek out items online by providing suggestions that closely match their interests. Recommender system, an information filtering technology employed in many items is presented in internet sites as per the interest of users, and is implemented in applications like movies, music, venue, books, research articles, tourism and social media normally. Recommender systems research is usually supported comparisons of predictive accuracy: the higher the evaluation scores, the higher the recommender. One amongst the leading approaches was the utilization of advice systems to proactively recommend scholarly papers to individual researchers. In today's world, time has more value and therefore the researchers haven't any much time to spend on trying to find the proper articles in line with their research domain. Recommender Systems are designed to suggest users the things that best fit the user needs and preferences. Recommender systems typically produce an inventory of recommendations in one among two ways -through collaborative or content-based filtering. Additionally, both the general public and also the non-public used descriptive metadata are used. The scope of the advice is therefore limited to variety of documents which are either publicly available or which are granted copyright permits. Recommendation systems (RS) support users and developers of varied computer and software systems to beat information overload, perform information discovery tasks and approximate computation, among others.
The study LiFi (Light Fidelity) demonstrates about how can we use this technology as a medium of communication similar to Wifi . This is the latest technology proposed by Harold Haas in 2011. It explains about the process of transmitting data with the help of illumination of an Led bulb and about its speed intensity to transmit data. Basically in this paper, author will discuss about the technology and also explain that how we can replace from WiFi to LiFi . WiFi generally used for wireless coverage within the buildings while LiFi is capable for high intensity wireless data coverage in limited areas with no obstacles .This research paper represents introduction of the Lifi technology,performance,modulation and challenges. This research paper can be used as a reference and knowledge to develop some of LiFitechnology.
Social media platform and Our right to privacyvivatechijri
The advancement of Information Technology has hastened the ability to disseminate information across the globe. In particular, the recent trends in ‘Social Networking’ have led to a spark in personally sensitive information being published on the World Wide Web. While such socially active websites are creative tools for expressing one’s personality it also entails serious privacy concerns. Thus, Social Networking websites could be termed a double edged sword. It is important for the law to keep abreast of these developments in technology. The purpose of this paper is to demonstrate the limits of extending existing laws to battle privacy intrusions in the Internet especially in the context of social networking. It is suggested that privacy specific legislation is the most appropriate means of protecting online privacy. In doing so it is important to maintain a balance between the competing right of expression, the failure of which may hinder the reaping of benefits offered by Internet technology
THE USABILITY METRICS FOR USER EXPERIENCEvivatechijri
THE USABILITY METRICS FOR USER EXPERIENCE was innovatively created by Google engineers and it is ready for production in record time. The success of Google is to attributed the efficient search algorithm, and also to the underlying commodity hardware. As Google run number of application then Google’s goal became to build a vast storage network out of inexpensive commodity hardware. So Google create its own file system, named as THE USABILITY METRICS FOR USER EXPERIENCE that is GFS. THE USABILITY METRICS FOR USER EXPERIENCE is one of the largest file system in operation. Generally THE USABILITY METRICS FOR USER EXPERIENCE is a scalable distributed file system of large distributed data intensive apps. In the design phase of THE USABILITY METRICS FOR USER EXPERIENCE, in which the given stress includes component failures , files are huge and files are mutated by appending data. The entire file system is organized hierarchically in directories and identified by pathnames. The architecture comprises of multiple chunk servers, multiple clients and a single master. Files are divided into chunks, and that is the key design parameter. THE USABILITY METRICS FOR USER EXPERIENCE also uses leases and mutation order in their design to achieve atomicity and consistency. As of there fault tolerance, THE USABILITY METRICS FOR USER EXPERIENCE is highly available, replicas of chunk servers and master exists.
Google File System was innovatively created by Google engineers and it is ready for production in record time. The success of Google is to attributed the efficient search algorithm, and also to the underlying commodity hardware. As Google run number of application then Google’s goal became to build a vast storage network out of inexpensive commodity hardware. So Google create its own file system, named as Google File System that is GFS. Google File system is one of the largest file system in operation. Generally Google File System is a scalable distributed file system of large distributed data intensive apps. In the design phase of Google file system, in which the given stress includes component failures , files are huge and files are mutated by appending data. The entire file system is organized hierarchically in directories and identified by pathnames. The architecture comprises of multiple chunk servers, multiple clients and a single master. Files are divided into chunks, and that is the key design parameter. Google File System also uses leases and mutation order in their design to achieve atomicity and consistency. As of there fault tolerance, Google file system is highly available, replicas of chunk servers and master exists.
A Study of Tokenization of Real Estate Using Blockchain Technologyvivatechijri
Real estate is by far one of the most trusted investments that people have preferred, being a lucrative investment it provides a steady source of income in the form of lease and rents. Although there are numerous advantages, one of the key downsides of real estate investments is lack of liquidity. Thus, even though global real estate investments amount to about twice the size of investments in stock markets, the number of investors in the real estate market is significantly lower. Block chain technology has real potential in addressing the issues of liquidity and transparency, opening the market to even retail investors. Owing to the functionality and flexibility of creating Security Tokens, which are backed by real-world assets, real estate can be made liquid with the help of Special Purpose Vehicles. Tokens of ERC 777 standard, which represent fractional ownership of the real estate can be purchased by an investor and these tokens can also be listed on secondary exchanges. The robustness of Smart Contracts can enable the efficient transfer of tokens and seamless distribution of earnings amongst the investors. This work describes Ethereum blockchainbased solutions to make the existing Real Estate investment system much more efficient.
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
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In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
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This document will discuss each of the underlying technologies to create and implement an e- commerce website.
FACE DETECTION AND FEATURE EXTRACTION FOR FACIAL EMOTION DETECTION
1. VIVA-Tech International Journal for Research and Innovation Volume 1, Issue 4 (2021)
ISSN(Online): 2581-7280 Article No. X
PP XX-XX
VIVA Institute of Technology
9th
National Conference on Role of Engineers in Nation Building – 2021 (NCRENB-2021)
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FACE DETECTION AND FEATURE EXTRACTION FOR FACIAL
EMOTION DETECTION
Chetan Bhosale1
, Disha Jariwala2
, Tejas Keni3
, Karishma Raut4
1
(EXTC, Viva Institute of Technology/ Mumbai University, India)
2
(EXTC, Viva Institute of Technology/ Mumbai University, India)
3
(EXTC, Viva Institute of Technology/ Mumbai University, India)
4
(EXTC, Viva Institute of Technology/ Mumbai University, India)
Abstract : Facial emotion Recognition has been a major issue and an advanced area of research in the field of Human-
Machine 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.
Keywords - Emotion recognition, CNN, Machine learning, Python, AI
1.INTRODUCTION
Mental illness has a profound effect on human performance, health, and quality of life. Getting early warning of depression
or other mental illness is a challenge.
Generally, the availability of emotional information is required for emotional awareness .The elements of emotional
information include a variety of physical or behavioral responses as well as changes in mood, including internal and
external emotional factors.
Human emotion recognition plays an important role in the interpersonal relationship and for detecting user's state of mind.
The automatic recognition of emotions has been an active research topic from early times,therefore, there are several
advances made in this field. Emotions are reflected from hand,speech, gestures of the body and through facial expressions.
Hence extracting and understanding of emotion is very essential for the interaction between human and machine
communication[1].
Facial recognition (FER) has emerged as an important area of research over the past two decades. Facial expressions are
one of the quickest, most natural, and powerful ways for people to communicate their intentions and emotions. The FER
system can be used for many important applications such as driver safety, health care, video conferencing, virtual reality,
and cognitive science etc.
Often, facial expressions can be divided into neutral, anger, disgust, fear, surprise, sadness and joy. Recent research shows
that young people 'ability to read other people's feelings and emotions is diminished by the increased use of digital
devices[2]. Therefore, it is important to develop an FER system that accurately detects facial expressions in real time.
2. VIVA-Tech International Journal for Research and Innovation Volume 1, Issue 4 (2021)
ISSN(Online): 2581-7280 Article No. X
PP XX-XX
VIVA Institute of Technology
9th
National Conference on Role of Engineers in Nation Building – 2021 (NCRENB-2021)
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www.viva-technology.org/New/IJRI
Fig 1.1 : 8 emotion database examples [3]
An important platform where we see the importance of emotionally acquiring through business promotions. Most
businesses thrive on customer service in all products and services. If a smart installation program can capture and identify
real-time feelings based on a user’s photo or video, they can decide whether the customer liked or disliked the product or
offer.
In recent years, in-depth learning has been a great success and is effective because of the effect achieved by its
properties that allow for automatic release of features and isolation such as the convolutional neural network CNN and
the repetitive neural RNN network[4]
2.METHODOLOGY
2.1 PROPOSED METHOD
Emotion Recognition System comprises of three principle steps. Initial step is to recognize the face area from the gained
picture and afterward preprocessed in order to limit the natural and different varieties in the picture. The following stage
is to remove articulation highlights which are then ordered in the third step. The classifier gives the yield of the articulation
which is perceived. The flowchart is shown below:-
Fig 2.1: :Flowchart of the Proposed method.
3. VIVA-Tech International Journal for Research and Innovation Volume 1, Issue 4 (2021)
ISSN(Online): 2581-7280 Article No. X
PP XX-XX
VIVA Institute of Technology
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National Conference on Role of Engineers in Nation Building – 2021 (NCRENB-2021)
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2.2 Face Detection
Paul Viola and Michael Jones in their paper, “Rapid Object Detection using a Boosted Cascade of Simple Features” in
2001 proposed that Object Detection using Haar feature- elements based cascade classifiers is an efficient object detection
method.
It is a machine learning based methododology where a cascade function is trained from a plenty of positive and negative
images.Then it is used to detect objects in other different images.
Here we will work with face detection.The algorithm needs a plenty of positive images (images of faces) and negative
images (images without faces) to train the classifier as per requirements. Then we have to extract features from it. For
this, haar features shown in below image(Fig 2.1) are used. They are just like our convolutional kernel. Every facial
feature represent a single value obtained by subtracting sum of pixels under white rectangle from sum of pixels under
black rectangle. [6]
A standard cascade classifier is a very effective way of Viola and Jones to get a face. In many cases, the task of finding
an object with a solid structure can be addressed in this way, not just in the face. The cascade classifier is a tree-based
technology, in which Viola and Jones used things like Haar to find a human face. [7]
The Haar-like features are shown in Figure
Fig 2.2: Haar like features
2.3 Feature Extraction
Facial feature extraction is the method of extracting facial features such as eyes, nose, mouth, etc. from a individual's face
image. The extraction of a facial feature is very important in the implementation of processing techniques such as facial
recognition, face tracking or facial expression recognition. [8]
Localization and detection of eye is important among all the facial features, from which locations of all different facial
features are identified.
We use an algorithm called face landmark estimation for localization. There are lots of ways to do this, but we are going
to use the approach invented in 2014 by Vahid Kazemi and Josephine Sullivan. [9]
Further,we will come up with 68 specific points (these are called landmarks) that exist on every face — the top of the
chin, the outside edge of each eye, the inner edge of each eyebrow and many more. Further, we are going to train a
machine learning(ML) algorithm to be able to find these 68 specific points on any face[10]
4. VIVA-Tech International Journal for Research and Innovation Volume 1, Issue 4 (2021)
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Fig 2.2: Facial Landmark Points[11]
3.Result and Discussion
Implementation is done on two basic things which is required to implement for facial emotion detection first one is face
detection
For emotion detection first important thing is to detect face and with the help of face, emotion is detected. For face
detection there are many methods are used but in our Proposed system Haar cascade classifier is used. Haar Cascade
classifier is used to detect face from the image, feature from face or body. It is also used to detect eyes, smile, full body,
half body etc. If face is detected the face detection part in image is shown by a rectangle
First required XML classifiers need to be loaded. Further,load our input image (or video) in grayscale mode. Then it will
search for face, If faces are found, it returns the positions of detected faces as Rectangle(x,y,w,h) (Fig 3.1). Once we get
thelocations, we can create a ROI for the face.
Fig 3.1 : Output of Face detetction
For Feature extraction process first face recognition library is loaded. Input image or video which is coming from the
face detection part is loaded. Then facial landmark algorithm is applied on input image (or video). If feature extraction
part is applied on the image it will show an output with 68 landmark points on the image. The facial feature parts are
shown here are chin, eyes, eyebrows, nose and lips etc (Fig 3.2).
The facial landmark point is shown by drawing circle on image. Position of circle is return by circle (image, center, radius,
color, thickness)
5. VIVA-Tech International Journal for Research and Innovation Volume 1, Issue 4 (2021)
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Fig 3.2 Output of Feature Extraction
4.CONCLUSION .
An image processing techniques is developed for extraction of facial landmark features .We successfully detected the face
using Haar cascade classifier and then extracted the features. This can be further used for detection of facial emotion .
Future work should entail investigating more accurate detection method that gives better computational efficiency.[12]
Acknowledgement
This project has cost a large amount of work, research and dedication. Still, implementation would not have been possible
without the support of our faculties. I would like to express our gratitude and appreciation to all of them. First of all I am
thankful to our project guide Prof. Karishma Raut for her technological and mental support and for providing necessary
guidance concerning projects implementation. I would like to express our sincere thanks towards all other faculty members
who devoted their time and knowledge in the implementation of this project. Also I would like to thank our HOD Prof.
Archana Ingle for her kind support. .I declare that I have respected and regulated0 principles of academic honesty and
integrity and have not misrepresented or fabricated or falsified any idea/data/fact/source in the submission.
REFERENCES
[1] A. A. Varghese, J. P. Cherian and J. J. Kizhakkethottam, "Overview on emotion recognition system," 2015 International Conference on Soft-
Computing and Networks Security (ICSNS), Coimbatore, 2015, pp. 1-5, doi: 10.1109/ICSNS.2015.7292443.
[2] Awais Mahmood, Shariq Hussain, Khalid Iqbal, Wail S. Elkilani; “Recognition of Facial Expressions under Varying Conditions.
Using Dual-Feature Fusion”; Mathematical Problems in Engineering, vol. 2019, Article ID 9185481
[3] Chen, Junkai & Chen, Zenghai & Chi, Zheru & Fu, Hong. (2014). Facial Expression Recognition Based on Facial Components Detection and HOG
Features.
[4] Wafa Mellouk, Wahida Handouzi(2020). Facial emotion recognition using deep learning: review and insights.
[5] Viola, Paul & Jones, Michael. (2001). Rapid Object Detection using a Boosted Cascade of Simple Features. IEEE Conf Comput Vis Pattern Recognit.
1. I-511. 10.1109/CVPR.2001.990517.
[6] Mehtab, Sidra & Sen, Jaydip. (2020). Face Detection Using OpenCV and Haar Cascades Classifiers. 10.13140/RG.2.2.26708.83840.
[7] Mayuri Munnolimath,, Saba Kausar, Shehza Hussain,Varsha Lokesh,Dr. R. Kanagavalli.;”Virtuala-The Smart Glass”; JETIR May 2019.
[8] S. R.Benedict and J S. Kumar, "Geometric shaped facial feature extraction for face recognition," 2016 IEEE International Conference on Advances
in Computer Applications (ICACA)” , Coimbatore, 2016, pp. 275-278, doi: 10.1109/ICACA.2016.7887965.
6. VIVA-Tech International Journal for Research and Innovation Volume 1, Issue 4 (2021)
ISSN(Online): 2581-7280 Article No. X
PP XX-XX
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National Conference on Role of Engineers in Nation Building – 2021 (NCRENB-2021)
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[9] Kazemi, Vahid & Sullivan, Josephine. (2014); “ One Millisecond Face Alignment with an Ensemble of Regression Trees”,10.13140/2.1.1212.2243
[10] Anushka Waingankar, Akash Upadhyay, Ruchi Shah, Nevil Pooniwala, Prashant Kasambe; “Face Recognition based Attendance Management
System using Machine Learning”, International Research Journal of Engineering and Technology (IRJET),2018
[11] Healy, Michael & Donovan, Ryan & Walsh, Paul & Zheng, Huiru. (2019); “ A Machine Learning Emotion Detection Platform to Support Affective
Well Being”, 10.1109/BIBM.2018.8621562
[12] James Pao”Emotion Detection through Facial Feature Recognition”
.