Download or read book A Multi modal Approach for Face Modeling and Recognition written by Mohammad Hossein Mahoor and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation describes a new methodology for multi-modal (2-D + 3-D) face modeling and recognition. There are advantages in using each modality for face recognition. For example, the problems of pose variation and illumination condition, which cannot be resolved easily by using the 2-D data, can be handled by using the 3-D data. However, texture, which is provided by 2-D data, is an important cue that cannot be ignored. Therefore, we use both the 2-D and 3-D modalities for face recognition and fuse the results of face recognition by each modality to boost the overall performance of the system. In this dissertation, we consider two different cases for multi-modal face modeling and recognition. In the first case, the 2-D and 3-D data are registered. In this case we develop a unified graph model called Attributed Relational Graph (ARG) for face modeling and recognition. Based on the ARG model, the 2-D and 3-D data are included in a single model. The developed ARG model consists of nodes, edges, and mutual relations. The nodes of the graph correspond to the landmark points that are extracted by an improved Active Shape Model (ASM) technique. In order to extract the facial landmarks robustly, we improve the Active Shape Model technique by using the color information. Then, at each node of the graph, we calculate the response of a set of log-Gabor filters applied to the facial image texture and shape information (depth values); these features are used to model the local structure of the face at each node of the graph. The edges of the graph are defined based on Delaunay triangulation and a set of mutual relations between the sides of the triangles are defined. The mutual relations boost the final performance of the system. The results of face matching using the 2-D and 3-D attributes and the mutual relations are fused at the score level. In the second case, the 2-D and 3-D data are not registered. This lack of registration could be due to different reasons such as time lapse between the data acquisitions. Therefore, the 2-D and 3-D modalities are modeled independently. For the 3-D modality, we developed a fully automated system for 3-D face modeling and recognition based on ridge images. The problem with shape matching approaches such as Iterative Closest Points (ICP) or Hausdorff distance is the computational complexity. We model the face by 3-D binary ridge images and use them for matching. In order to match the ridge points (either using the ICP or the Hausdorff distance), we extract three facial landmark points: namely, the two inner corners of the eyes and the tip of the nose, on the face surface using the Gaussian curvature. These three points are used for initial alignment of the constructed ridge images. As a result of using ridge points, which are just a fraction of the total points on the surface of the face, the computational complexity of the matching is reduced by two orders of magnitude. For the 2-D modality, we model the face using an Attributed Relational Graph. The results of the 2-D and 3-D matching are fused at the score level. There are various techniques to fuse the 2-D and 3-D modalities. In this dissertation, we fuse the matching results at the score level to enhance the overall performance of our face recognition system. We compare the Dempster-Shafer theory of evidence and the weighted sum rule for fusion. We evaluate the performance of the above techniques for multi-modal face recognition on various databases such as Gavab range database, FRGC (Face Recognition Grand Challenge) V2.0, and the University of Miami face database.

Download or read book Advances in Biometrics written by David Zhang and published by Springer Science & Business Media. This book was released on 2006-02-10 with total page 814 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the International Conference on Biometrics, ICB 2006, held in Hong Kong, China in January 2006. The book includes 104 revised full papers covering such areas of biometrics as the face, fingerprint, iris, speech and signature, biometric fusion and performance evaluation, gait, keystrokes, and more. In addition the results of the Face Authentication Competition (FAC 2006) are also announced in this volume.

Download or read book Face Biometrics for Personal Identification written by Besma Abidi and published by Springer Science & Business Media. This book was released on 2007-04-08 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides ample coverage of theoretical and experimental state-of-the-art work as well as new trends and directions in the biometrics field. It offers students and software engineers a thorough understanding of how some core low-level building blocks of a multi-biometric system are implemented. While this book covers a range of biometric traits, its main emphasis is placed on multi-sensory and multi-modal face biometrics algorithms and systems.

Download or read book Learning Techniques for Multi modal Facial Analysis written by Munawar Hayat and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Face and facial expression recognition are two important facial analysis tasks with numerous real life applications. This dissertation investigates the suitability of different data modalities for these two tasks. Specifically, the dissertation first proposes a method for the automatic analysis of textured 3D videos for facial expression recognition. The task of face recognition is then considered across multiple data modalities which include 3D static images and videos, RGB-D images acquired from low cost Kinect sensor and low quality grey scale images acquired from surveillance cameras. The dissertation is organized as a set of papers already published or submitted to journals or internationally refereed conferences. The dissertation first evaluates and compares existing methods of spatiotemporal feature description for 2D video-based facial expression recognition. It then presents an automatic framework, which exploits the dynamics of textured 3D videos for the recognizing six discrete facial expressions. Specifically, local video-patches of variable lengths are extracted from numerous locations of the training videos and represented as points on the Grassmannian manifold. An efficient graph-based spectral clustering algorithm is proposed to separately cluster these points for every expression class. Using a valid Grassmannian kernel function, the resulting cluster centers are embedded into a Reproducing Kernel Hilbert Space (RKHS) where six binary SVM models are learnt for classification. The dissertation then proposes manifold learning, deep learning and discriminative learning techniques for face recognition across multiple data modalities. First, a computationally efficient low level feature description method is proposed for face recognition from 3D static images. A method for the spatiotemporal evaluation of 3D videos is then presented. Face recognition from RGB-D images acquired from Kinect sensor is then considered as an image set classification problem. A method for the compact description of image sets using Riemannian geometry is proposed in this regards. For classification, SVM models are learnt on the Lie group of Riemannian manifold. The dissertation then finally considers face recognition from low quality imagery acquired from easily installable video surveillance cameras. Face recognition from this data modality is also studied under the framework of image set classification. For this purpose, two independent high performing methods are proposed. The first method learns deep reconstruction models, which can automatically discover the underlying complex geometric structure of the images in an image set. The second method empowers well developed binary classifiers for the task of multi-class image set classification. Compared to the existing binary to multiclass extension strategies, the proposed method is very efficient since it only trains few binary classifiers and uses very few images for the training of each of these classifiers.

Download or read book Multi Object Modelling of the Face written by Hanan Salam and published by . This book was released on 2013 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: The work in this thesis deals with the problematic of face modeling for the purpose of facial analysis.In the first part of this thesis, we proposed the Multi-Object Facial Actions Active Appearance Model (AAM). The specificity of the proposed model is that different parts of the face are treated as separate objects and eye movements (gaze and blink) are extrinsically parameterized. This increases the generalization capabilities of classical AAM.The second part of the thesis concerns the use of face modeling in the context of expression and emotion recognition. First we have proposed a system for the recognition of facial expressions in the form of Action Units (AU). Our contribution concerned mainly the extraction of AAM features of which we have opted for the use of local models.The second system concerns multi-modal recognition of four continuously valued affective dimensions. We have proposed a system that fuses audio, context and visual features and gives as output the four emotional dimensions. We contribute to the system by finding the precise localization of the facial features. Accordingly, we propose the Multi-Local AAM. This model combines extrinsically a global model of the face and a local one of the mouth through the computation of projection errors on the same global AAM.

Download or read book Multibiometrics for Human Identification written by Bir Bhanu and published by Cambridge University Press. This book was released on 2011-04-29 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: In today's security-conscious society, real-world applications for authentication or identification require a highly accurate system for recognizing individual humans. The required level of performance cannot be achieved through the use of a single biometric such as face, fingerprint, ear, iris, palm, gait or speech. Fusing multiple biometrics enables the indexing of large databases, more robust performance and enhanced coverage of populations. Multiple biometrics are also naturally more robust against attacks than single biometrics. This book addresses a broad spectrum of research issues on multibiometrics for human identification, ranging from sensing modes and modalities to fusion of biometric samples and combination of algorithms. It covers publicly available multibiometrics databases, theoretical and empirical studies on sensor fusion techniques in the context of biometrics authentication, identification and performance evaluation and prediction.

Download or read book 3D Face Modeling Analysis and Recognition written by Mohamed Daoudi and published by John Wiley & Sons. This book was released on 2013-06-11 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: 3D Face Modeling, Analysis and Recognition presents methodologies for analyzing shapes of facial surfaces, develops computational tools for analyzing 3D face data, and illustrates them using state-of-the-art applications. The methodologies chosen are based on efficient representations, metrics, comparisons, and classifications of features that are especially relevant in the context of 3D measurements of human faces. These frameworks have a long-term utility in face analysis, taking into account the anticipated improvements in data collection, data storage, processing speeds, and application scenarios expected as the discipline develops further. The book covers face acquisition through 3D scanners and 3D face pre-processing, before examining the three main approaches for 3D facial surface analysis and recognition: facial curves; facial surface features; and 3D morphable models. Whilst the focus of these chapters is fundamentals and methodologies, the algorithms provided are tested on facial biometric data, thereby continually showing how the methods can be applied. Key features: • Explores the underlying mathematics and will apply these mathematical techniques to 3D face analysis and recognition • Provides coverage of a wide range of applications including biometrics, forensic applications, facial expression analysis, and model fitting to 2D images • Contains numerous exercises and algorithms throughout the book

Download or read book Face Processing Advanced Modeling and Methods written by Wenyi Zhao and published by Elsevier. This book was released on 2011-07-28 with total page 755 pages. Available in PDF, EPUB and Kindle. Book excerpt: Major strides have been made in face processing in the last ten years due to the fast growing need for security in various locations around the globe. A human eye can discern the details of a specific face with relative ease. It is this level of detail that researchers are striving to create with ever evolving computer technologies that will become our perfect mechanical eyes. The difficulty that confronts researchers stems from turning a 3D object into a 2D image. That subject is covered in depth from several different perspectives in this volume. Face Processing: Advanced Modeling and Methods begins with a comprehensive introductory chapter for those who are new to the field. A compendium of articles follows that is divided into three sections. The first covers basic aspects of face processing from human to computer. The second deals with face modeling from computational and physiological points of view. The third tackles the advanced methods, which include illumination, pose, expression, and more. Editors Zhao and Chellappa have compiled a concise and necessary text for industrial research scientists, students, and professionals working in the area of image and signal processing. - Contributions from over 35 leading experts in face detection, recognition and image processing - Over 150 informative images with 16 images in FULL COLOR illustrate and offer insight into the most up-to-date advanced face processing methods and techniques - Extensive detail makes this a need-to-own book for all involved with image and signal processing

Download or read book Computational Intelligence and Information Technology written by Vinu Das and published by Springer Science & Business Media. This book was released on 2013-01-02 with total page 900 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the First International Conference on Computational Intelligence and Information Technology, CIIT 2011, held in Pune, India, in November 2011. The 58 revised full papers, 67 revised short papers, and 32 poster papers presented were carefully reviewed and selected from 483 initial submissions. The papers are contributed by innovative academics and industrial experts in the field of computer science, information technology, computational engineering, mobile communication and security and offer a stage to a common forum, where a constructive dialog on theoretical concepts, practical ideas and results of the state of the art can be developed.

Download or read book Handbook of Pattern Recognition and Computer Vision written by C. H. Chen and published by World Scientific. This book was released on 1999 with total page 1045 pages. Available in PDF, EPUB and Kindle. Book excerpt: The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference.

Download or read book Affect and Emotion in Human Computer Interaction written by Christian Peter and published by Springer. This book was released on 2008-08-25 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Affect and emotion play an important role in our everyday lives: They are present whatever we do, wherever we are, and wherever we go, without us being aware of them for much of the time. When it comes to interaction, be it with humans, technology, or humans via technology, we suddenly become more aware of emotion, either by seeing the other’s emotional expression, or by not getting an emotional response while anticipating one. Given this, it seems only sensible to explore affect and emotion in human-computer interaction, to investigate the underlying principles, to study the role they play, to develop methods to quantify them, and to finally build applications that make use of them. This is the research field for which, over ten years ago, Rosalind Picard coined the phrase "affective computing". The present book provides an account of the latest work on a variety of aspects related to affect and emotion in human-technology interaction. It covers theoretical issues, user experience and design aspects as well as sensing issues, and reports on a number of affective applications that have been developed in recent years.

Download or read book Biometrics in Identity Management written by Shimon K. Modi and published by Artech House. This book was released on 2011 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: In todayOCOs digital infrastructure we have to interact with an increasing number of systems, both in the physical and virtual world. Identity management (IdM) -- the process of identifying an individual and controlling access to resources based on their associated privileges -- is becoming progressively complex. This has brought the spotlight on the importance of effective and efficient means of ascertaining an individualOCOs identity. Biometric technologies like fingerprint recognition, face recognition, iris recognition etc. have a long history of use in law enforcement applications and are now transitioning towards commercial applications like password replacements, ATM authentication and others.This unique book provides you with comprehensive coverage of commercially available biometric technologies, their underlying principles, operational challenges and benefits, and deployment considerations. It also offers a look at the future direction these technologies are taking. By focusing on factors that drive the practical implementation of biometric technologies, this book serves to bridge the gap between academic researchers and industry practitioners. This book focuses on design, development, and deployment issues related to biometric technologies, including operational challenges, integration strategies, technical evaluations of biometric systems, standardization and privacy preserving principles, and several open questions which need to be answered for successful deployments."

Download or read book Computer Vision ECCV 2006 written by and published by Springer Science & Business Media. This book was released on 2006 with total page 665 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Pattern Recognition ICPR International Workshops and Challenges written by Alberto Del Bimbo and published by Springer Nature. This book was released on 2021-02-20 with total page 741 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 8-volumes set constitutes the refereed of the 25th International Conference on Pattern Recognition Workshops, ICPR 2020, held virtually in Milan, Italy and rescheduled to January 10 - 11, 2021 due to Covid-19 pandemic. The 416 full papers presented in these 8 volumes were carefully reviewed and selected from about 700 submissions. The 46 workshops cover a wide range of areas including machine learning, pattern analysis, healthcare, human behavior, environment, surveillance, forensics and biometrics, robotics and egovision, cultural heritage and document analysis, retrieval, and women at ICPR2020.

Download or read book Face Detection and Modeling for Recognition written by Rein-Lien Hsu and published by . This book was released on 2002 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book An Automated Multimodal Face Recognition System Based on Fusion of Face and Ear written by Lorenzo Luciano and published by . This book was released on 2009 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book New Approaches to Characterization and Recognition of Faces written by Peter Corcoran and published by BoD – Books on Demand. This book was released on 2011-08-01 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: As a baby, one of our earliest stimuli is that of human faces. We rapidly learn to identify, characterize and eventually distinguish those who are near and dear to us. We accept face recognition later as an everyday ability. We realize the complexity of the underlying problem only when we attempt to duplicate this skill in a computer vision system. This book is arranged around a number of clustered themes covering different aspects of face recognition. The first section presents an architecture for face recognition based on Hidden Markov Models; it is followed by an article on coding methods. The next section is devoted to 3D methods of face recognition and is followed by a section covering various aspects and techniques in video. Next short section is devoted to the characterization and detection of features in faces. Finally, you can find an article on the human perception of faces and how different neurological or psychological disorders can affect this.