Face Detection and Modeling for Recognition - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Face Detection and Modeling for Recognition write by Rein-Lien Hsu. This book was released on 2002. Face Detection and Modeling for Recognition available in PDF, EPUB and Kindle. Face recognition has received substantial attention from researchers in biometrics, computer vision, pattern recognition, and cognitive psychology communities because of the increased attention being devoted to security, man-machine communication, content-based image retrieval, and image/video coding. We have proposed two automated recognition paradigms to advance face recognition technology. Three major tasks involved in face recognition systems are: (i) face detection, (ii) face modeling, and (iii) face matching. We have developed a face detection algorithm for color images in the presence of various lighting conditions as well as complex backgrounds. Our detection method first corrects the color bias by a lighting compensation technique that automatically estimates the parameters of reference white for color correction. We overcame the difficulty of detecting the low-luma and high-luma skin tones by applying a nonlinear transformation to the Y CbCr color space. Our method generates face candidates based on the spatial arrangement of detected skin patches. We constructed eye, mouth, and face boundary maps to verify each face candidate. Experimental results demonstrate successful detection of faces with different sizes, color, position, scale, orientation, 3D pose, and expression in several photo collections. 3D human face models augment the appearance-based face recognition approaches to assist face recognition under the illumination and head pose variations. For the two proposed recognition paradigms, we have designed two methods for modeling human faces based on (i) a generic 3D face model and an individual's facial measurements of shape and texture captured in the frontal view, and (ii) alignment of a semantic face graph, derived from a generic 3D face model, onto a frontal face image.
Face Detection and Gesture Recognition for Human-Computer Interaction
Face Detection and Gesture Recognition for Human-Computer Interaction - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Face Detection and Gesture Recognition for Human-Computer Interaction write by Ming-Hsuan Yang. This book was released on 2012-12-06. Face Detection and Gesture Recognition for Human-Computer Interaction available in PDF, EPUB and Kindle. Traditionally, scientific fields have defined boundaries, and scientists work on research problems within those boundaries. However, from time to time those boundaries get shifted or blurred to evolve new fields. For instance, the original goal of computer vision was to understand a single image of a scene, by identifying objects, their structure, and spatial arrangements. This has been referred to as image understanding. Recently, computer vision has gradually been making the transition away from understanding single images to analyzing image sequences, or video understanding. Video understanding deals with understanding of video sequences, e. g. , recognition of gestures, activities, facial expressions, etc. The main shift in the classic paradigm has been from the recognition of static objects in the scene to motion-based recognition of actions and events. Video understanding has overlapping research problems with other fields, therefore blurring the fixed boundaries. Computer graphics, image processing, and video databases have obvious overlap with computer vision. The main goal of computer graphics is to gener ate and animate realistic looking images, and videos. Researchers in computer graphics are increasingly employing techniques from computer vision to gen erate the synthetic imagery. A good example of this is image-based rendering and modeling techniques, in which geometry, appearance, and lighting is de rived from real images using computer vision techniques. Here the shift is from synthesis to analysis followed by synthesis.
Face Analysis, Modeling and Recognition Systems
Face Analysis, Modeling and Recognition Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Face Analysis, Modeling and Recognition Systems write by Tudor Barbu. This book was released on 2011-10-03. Face Analysis, Modeling and Recognition Systems available in PDF, EPUB and Kindle. The purpose of this book, entitled Face Analysis, Modeling and Recognition Systems is to provide a concise and comprehensive coverage of artificial face recognition domain across four major areas of interest: biometrics, robotics, image databases and cognitive models. Our book aims to provide the reader with current state-of-the-art in these domains. The book is composed of 12 chapters which are grouped in four sections. The chapters in this book describe numerous novel face analysis techniques and approach many unsolved issues. The authors who contributed to this book work as professors and researchers at important institutions across the globe, and are recognized experts in the scientific fields approached here. The topics in this book cover a wide range of issues related to face analysis and here are offered many solutions to open issues. We anticipate that this book will be of special interest to researchers and academics interested in computer vision, biometrics, image processing, pattern recognition and medical diagnosis.
Handbook of Face Recognition
Handbook of Face Recognition - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Handbook of Face Recognition write by Stan Z. Li. This book was released on 2005-12-06. Handbook of Face Recognition available in PDF, EPUB and Kindle. Although the history of computer-aided face recognition stretches back to the 1960s, automatic face recognition remains an unsolved problem and still offers a great challenge to computer-vision and pattern recognition researchers. This handbook is a comprehensive account of face recognition research and technology, written by a group of leading international researchers. Twelve chapters cover all the sub-areas and major components for designing operational face recognition systems. Background, modern techniques, recent results, and challenges and future directions are considered. The book is aimed at practitioners and professionals planning to work in face recognition or wanting to become familiar with the state-of- the-art technology. A comprehensive handbook, by leading research authorities, on the concepts, methods, and algorithms for automated face detection and recognition. Essential reference resource for researchers and professionals in biometric security, computer vision, and video image analysis.
Face Detection and Modeling for Face Recognition
Face Detection and Modeling for Face Recognition - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Face Detection and Modeling for Face Recognition write by Hardik Bavishi. This book was released on 2006. Face Detection and Modeling for Face Recognition available in PDF, EPUB and Kindle. The primary aim of this research work is to study and implement Viola and Jones [3] based face detector, and provide possible improvement to the original algorithm. It also studies its possible integration with real time face recognition system. Recently, many new face detection algorithms have been published based on original Viola and Jones' face detector. Viola and Jones provided three novel approaches for constructing a rapid and robust real time face detection system. Using Haar-like features with unique integral image representation the computation of the features becomes extremely rapid. Using AdaBoost a strong non-linear classifier can be constructed, and only useful features out of large feature set can be extracted and used for face detection. Cascade of classifiers provides very positive solution for improvement of execution speed and also improves the accuracy of the whole system. By cascading classifiers, each stage is trained separately using different feature, in other word each stage focuses on particular feature. Using this technique a very rapid face detector can be created and its results are comparable with other state-of-the art technique. To understand the role of face detection system in real time face recognition system eigenfaces based real-time face recognition is evaluated.
