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Author : Xuejian Wang
Publisher :
Page : pages
File Size : 37,77 MB
Release : 2017
Category :
ISBN :
Author : Shaohua Kevin Zhou
Publisher : Springer Science & Business Media
Page : 244 pages
File Size : 13,99 MB
Release : 2006-10-11
Category : Computers
ISBN : 0387294864
Face recognition has been actively studied over the past decade and continues to be a big research challenge. Just recently, researchers have begun to investigate face recognition under unconstrained conditions. Unconstrained Face Recognition provides a comprehensive review of this biometric, especially face recognition from video, assembling a collection of novel approaches that are able to recognize human faces under various unconstrained situations. The underlying basis of these approaches is that, unlike conventional face recognition algorithms, they exploit the inherent characteristics of the unconstrained situation and thus improve the recognition performance when compared with conventional algorithms. Unconstrained Face Recognition is structured to meet the needs of a professional audience of researchers and practitioners in industry. This volume is also suitable for advanced-level students in computer science.
Author : Mahdi Jampour
Publisher :
Page : 140 pages
File Size : 17,4 MB
Release : 2018-02-03
Category :
ISBN : 9783330342583
Author : Qiang Ji
Publisher : Springer
Page : 152 pages
File Size : 19,10 MB
Release : 2015-03-18
Category : Computers
ISBN : 3319137379
This book constitutes the thoroughly refereed conference proceedings of the International Workshop on Face and Facial Expression Recognition from Real World Videos in conjunction with the 22nd International Conference on Pattern Recognition held in Stockholm, Sweden, in August 2014. The 11 revised full papers were carefully reviewed and selected from numerous submissions and cover topics such as Face Recognition, Face Alignment, Facial Expression Recognition and Facial Images.
Author : Xiang Yu
Publisher :
Page : 152 pages
File Size : 46,64 MB
Release : 2015
Category : Computer vision
ISBN :
Nowadays, facial landmark localization in unconstrained environments has attracted increasing attention in computer vision, which is a fundamental step in face recognition, expression recognition, face tracking, editing, face animation, etc. We firstly introduce the problem of facial landmark localization and its relevant canonical and state-of-the-art techniques. Among the existed methods, when facilitating to the facial images under unconstrained environments, they may encounter problems from the large pose variation, partial occlusion, unpredictable illumination, etc. We then separately investigate each of the pose variation and partial occlusion problems. To overcome the shape variation caused by the pose changes, we propose an optimized part mixture model to fast search in the pose manifold and a bi-stage cascaded deformable shape model to refine the local shape variance. For partial occlusion, we propose a consensus of occlusion-specific regressors framework, which resists from the occlusion due to the large amount of regressors and the particularly designed occlusion patterns. Further, we aim at building a unified framework to jointly deal with the pose and occlusion problems. A pose-conditioned hierarchical part based regression method is designed to condition the pose into several pre-defined subspaces and localize the key positions in a hierarchical way, in which the occlusion is detected by the part regressors and further propagated through the hierarchical structure. The proposed facial landmark localization methods have shown more promising performance than those state-of-the-arts in both accuracy and efficiency, compared on both lab-environmental databases and multiple challenging faces-in-the-wild databases. Our face alignment methods are further applied to some human-computer interaction (HCI) applications, i.e. user-defined expression recognition and face and gesture based visual deception detection. The improved results from the applications further validate the advantages of our method under all kinds of uncontrolled conditions.
Author : Michal Kawulok
Publisher : Springer
Page : 438 pages
File Size : 33,12 MB
Release : 2016-04-02
Category : Technology & Engineering
ISBN : 331925958X
This book presents the state-of-the-art in face detection and analysis. It outlines new research directions, including in particular psychology-based facial dynamics recognition, aimed at various applications such as behavior analysis, deception detection, and diagnosis of various psychological disorders. Topics of interest include face and facial landmark detection, face recognition, facial expression and emotion analysis, facial dynamics analysis, face classification, identification, and clustering, and gaze direction and head pose estimation, as well as applications of face analysis.
Author : Miloš Oravec
Publisher : BoD – Books on Demand
Page : 414 pages
File Size : 12,16 MB
Release : 2010-04-01
Category : Computers
ISBN : 9533070609
This book aims to bring together selected recent advances, applications and original results in the area of biometric face recognition. They can be useful for researchers, engineers, graduate and postgraduate students, experts in this area and hopefully also for people interested generally in computer science, security, machine learning and artificial intelligence. Various methods, approaches and algorithms for recognition of human faces are used by authors of the chapters of this book, e.g. PCA, LDA, artificial neural networks, wavelets, curvelets, kernel methods, Gabor filters, active appearance models, 2D and 3D representations, optical correlation, hidden Markov models and others. Also a broad range of problems is covered: feature extraction and dimensionality reduction (chapters 1-4), 2D face recognition from the point of view of full system proposal (chapters 5-10), illumination and pose problems (chapters 11-13), eye movement (chapter 14), 3D face recognition (chapters 15-19) and hardware issues (chapters 19-20).
Author : Ioanna-Ourania Stathopoulou
Publisher : IOS Press
Page : 268 pages
File Size : 12,92 MB
Release : 2010
Category : Computers
ISBN : 1607505967
It is generally known that human faces, as well as body motions and gestures, provide a wealth of information about a person, such as age, race, sex and emotional state. This monograph primarily studies the perception of facial expression of emotion, and secondarily of motion and gestures, with the purpose of developing a fully automated visual affect recognition system for use in modes of human/computer interaction. The book begins with a survey of the literature on emotion perception, followed by a decription of empirical studies conducted with human participants and the construction of a face image database . On the basis of this work, a visual affect recognition system was developed, consisting of two modules: a face detection subsystem and a facia expression recognition subsystem. Details of this system are demonstrated and analyzed, and extensive performance evaluations and test results are provided. Finally, current research avenues leading to visual affect recognition via analysis of body motin and gestures are also discussed."
Author : Manas Kamal Bhuyan
Publisher : CRC Press
Page : 417 pages
File Size : 14,4 MB
Release : 2019-11-05
Category : Computers
ISBN : 1351248375
The book familiarizes readers with fundamental concepts and issues related to computer vision and major approaches that address them. The focus of the book is on image acquisition and image formation models, radiometric models of image formation, image formation in the camera, image processing concepts, concept of feature extraction and feature selection for pattern classification/recognition, and advanced concepts like object classification, object tracking, image-based rendering, and image registration. Intended to be a companion to a typical teaching course on computer vision, the book takes a problem-solving approach.
Author : Mahmoud Hassaballah
Publisher : CRC Press
Page : 261 pages
File Size : 27,19 MB
Release : 2020-03-23
Category : Computers
ISBN : 1351003801
Deep learning algorithms have brought a revolution to the computer vision community by introducing non-traditional and efficient solutions to several image-related problems that had long remained unsolved or partially addressed. This book presents a collection of eleven chapters where each individual chapter explains the deep learning principles of a specific topic, introduces reviews of up-to-date techniques, and presents research findings to the computer vision community. The book covers a broad scope of topics in deep learning concepts and applications such as accelerating the convolutional neural network inference on field-programmable gate arrays, fire detection in surveillance applications, face recognition, action and activity recognition, semantic segmentation for autonomous driving, aerial imagery registration, robot vision, tumor detection, and skin lesion segmentation as well as skin melanoma classification. The content of this book has been organized such that each chapter can be read independently from the others. The book is a valuable companion for researchers, for postgraduate and possibly senior undergraduate students who are taking an advanced course in related topics, and for those who are interested in deep learning with applications in computer vision, image processing, and pattern recognition.