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Face analysis is essential for a large number of applications such as human-computer interaction or multimedia (e.g. content indexing and retrieval). Although many approaches are under investigation, performance under uncontrolled conditions is still not satisfactory. The variations that impact facial appearance (e.g. pose, expression, illumination, occlusion, motion blur) make it a difficult problem to solve. This book describes the progress towards this goal, from a core building block - landmark detection - to the higher level of micro and macro expression recognition. Specifically, the book addresses the modeling of temporal information to coincide with the dynamic nature of the face. It also includes a benchmark of recent solutions along with details about the acquisition of a dataset for such tasks.

Human face recognition (Computer science)

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In the opening chapter of Gesture Recognition: Performance, Applications and Features, the authors discuss gesture recognition and its role in the developing world of technology. The possibility of implementing a gesture detection application that works with people with special needs is examined, such as recognition of sign language for the hearing-impaired. Following this, the authors present their approach for face detection and tracking, user identification, facial feature extraction and head pose estimation as the low-level representation of facial gesture atomics. Additionally, an approach for a movement-based facial gestures recognition is presented, with results demonstrated through practical approaches. A later work explores spectral features from algebraic graph theory in static hand gesture recognition. Specifically, we apply a technique that uses the elements of the spectral matrix of the Laplacian to construct symmetric polynomials that are permutation invariants. The values of these polynomials can be used as graph features in a statistical learning pipeline that has the ability of distinguishing between distinct graphs and can reveal graph clusters. In the closing study, the authors developed two algorithms for the detection of pointing gestures and one approach for waving on this technological base and studied their functionality. The goal was to determine whether a combination of both strategies improves and stabilizes detection rates--

Human face recognition (Computer science) --- Gesture. --- Human-computer interaction.

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"In this riveting feat of reporting, Kashmir Hill illuminates the improbable rise of Clearview AI and how Hoan Ton-That, a computer engineer and Richard Schwartz, a Giuliani associate, launched a terrifying facial recognition app with society-altering potential. They were assisted by a cast of controversial characters, including conservative provocateur Charles Johnson and billionaire Trump backer Peter Thiel. The app can scan a blurry portrait, and, in just seconds, collect every instance of a person's online life. It can find your name, your social media profiles, your friends and family, even your home address (as well as photos of you that you may not even have known existed). The story of Clearview AI opens up a window into a larger, more urgent one about our tortured relationship to technology, the way it entertains and seduces us even as it steals our privacy and lays us bare to bad actors in politics, criminal justice, and tech. This technology has been quietly growing more powerful for decades. Ubiquitous in China and Russia, it was also developed by American companies, including Google and Facebook, who decided it was too radical to release. That did not stop Clearview. They gave demos of the tech to interested private investors and contracted it out to hundreds of law enforcement agencies around the country. American law enforcement, including the Department of Homeland Security, has already used it to arrest people for everything from petty theft to assault. Without regulation it could expand the reach of policing-as it has in China and Russia-to a terrifying, dystopian level"--

Human face recognition (Computer science) --- Social aspects. --- Clearview AI (Software company) --- History. --- Data privacy. --- Video surveillance --- Business ethics.

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This book provides an overview of different deep learning-based methods for face recognition and related problems. Specifically, the authors present methods based on autoencoders, restricted Boltzmann machines, and deep convolutional neural networks for face detection, localization, tracking, recognition, etc. The authors also discuss merits and drawbacks of available approaches and identifies promising avenues of research in this rapidly evolving field. Even though there have been a number of different approaches proposed in the literature for face recognition based on deep learning methods, there is not a single book available in the literature that gives a complete overview of these methods. The proposed book captures the state of the art in face recognition using various deep learning methods, and it covers a variety of different topics related to face recognition. The prerequisites for optimal use are the basic knowledge of pattern recognition, machine learning, probability theory, and linear algebra. This book is aimed at graduate students studying electrical engineering and/or computer science. Biometrics is a course that is widely offered at both undergraduate and graduate levels at many institutions around the world: This book can be used as a textbook for teaching topics related to face recognition. In addition, the work is beneficial to practitioners in industry who are working on biometrics-related problems. Nalini K. Ratha is Empire Innovation professor in the Department of Computer Science and Engineering at University at Buffalo (New York). He is co-author and co-editor, respectively, of the Springer books, Guide to Biometrics and Advances in Biometrics. Vishal M. Patel is Assistant Professor in the Department of Electrical and Computer Engineering at Johns Hopkins University (JHU). Rama Chellappa is Bloomberg Distinguished Professor in the Departments of Electrical and Computer Engineering and Biomedical Engineering at JHU. He is co-author and co-editor, respectively, of the Springer books, Unconstrained Face Recognition and Handbook of Remote Biometrics.

Optical data processing. --- Biometrics (Biology). --- Machine learning. --- Neural networks (Computer science) . --- Image Processing and Computer Vision. --- Biometrics. --- Machine Learning. --- Mathematical Models of Cognitive Processes and Neural Networks. --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Artificial intelligence --- Natural computation --- Soft computing --- Learning, Machine --- Machine theory --- Biological statistics --- Biology --- Biometrics (Biology) --- Biostatistics --- Biomathematics --- Statistics --- Optical computing --- Visual data processing --- Bionics --- Electronic data processing --- Integrated optics --- Photonics --- Computers --- Statistical methods --- Optical equipment --- Human face recognition (Computer science) --- Face recognition, Human (Computer science) --- Facial pattern recognition (Computer science) --- Optical pattern recognition

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This book constitutes the proceedings of the Third Workshop on Video Analytics for Audience Measurement, VAAM 2016, and the Second International Workshop on Face and Facial Expression Recognition from Real World Videos, FFER 2016, held at the 23rd International Conference on Pattern Recognition, ICPR 2016, in Cancun, Mexico, in December 2016. The 11 papers presented in this volume were carefully reviewed and selected from 13 submissions. They deal with: re-identification; consumer behavior analysis; utilizing pupillary response for task difficulty measurement; logo detection; saliency prediction; classification of facial expressions; face recognition; face verification; age estimation; super resolution; pose estimation; and pain recognition. .

Computer science. --- Special purpose computers. --- Computer security. --- Computers. --- Artificial intelligence. --- Computer graphics. --- Computer Science. --- Computer Imaging, Vision, Pattern Recognition and Graphics. --- Information Systems and Communication Service. --- Artificial Intelligence (incl. Robotics). --- Systems and Data Security. --- Special Purpose and Application-Based Systems. --- Automatic drafting --- Graphic data processing --- Graphics, Computer --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer privacy --- Computer system security --- Computer systems --- Computers --- Cyber security --- Cybersecurity --- Electronic digital computers --- Security of computer systems --- Special purpose computers --- Informatics --- Security measures --- Protection of computer systems --- Protection --- Computer art --- Graphic arts --- Electronic data processing --- Engineering graphics --- Image processing --- Bionics --- Cognitive science --- Digital computer simulation --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Cybernetics --- Calculators --- Cyberspace --- Data protection --- Security systems --- Hacking --- Science --- Digital techniques --- Computer vision. --- Information systems. --- Software engineering. --- Artificial Intelligence. --- Computer software engineering --- Engineering --- Machine vision --- Vision, Computer --- Artificial intelligence --- Pattern recognition systems --- Human face recognition (Computer science) --- Optical pattern recognition --- Digital video --- Face recognition, Human (Computer science) --- Facial pattern recognition (Computer science) --- Optical data processing. --- Optical computing --- Visual data processing --- Integrated optics --- Photonics --- Optical equipment