Kernel Learning Algorithms For Face Recognition

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Kernel Learning Algorithms for Face Recognition

Author : Jun-Bao Li
Publisher : Springer Science & Business Media
ISBN 13 : 1461401615
Total Pages : 232 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Kernel Learning Algorithms for Face Recognition by : Jun-Bao Li

Download or read book Kernel Learning Algorithms for Face Recognition written by Jun-Bao Li and published by Springer Science & Business Media. This book was released on 2013-09-07 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced kernel learning algorithms and its application on face recognition. This book also focuses on the theoretical deviation, the system framework and experiments involving kernel based face recognition. Included within are algorithms of kernel based face recognition, and also the feasibility of the kernel based face recognition method. This book provides researchers in pattern recognition and machine learning area with advanced face recognition methods and its newest applications.

Computer Vision -- ECCV 2010

Author : Kostas Daniilidis
Publisher : Springer Science & Business Media
ISBN 13 : 364215560X
Total Pages : 836 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Computer Vision -- ECCV 2010 by : Kostas Daniilidis

Download or read book Computer Vision -- ECCV 2010 written by Kostas Daniilidis and published by Springer Science & Business Media. This book was released on 2010-08-30 with total page 836 pages. Available in PDF, EPUB and Kindle. Book excerpt: The six-volume set comprising LNCS volumes 6311 until 6313 constitutes the refereed proceedings of the 11th European Conference on Computer Vision, ECCV 2010, held in Heraklion, Crete, Greece, in September 2010. The 325 revised papers presented were carefully reviewed and selected from 1174 submissions. The papers are organized in topical sections on object and scene recognition; segmentation and grouping; face, gesture, biometrics; motion and tracking; statistical models and visual learning; matching, registration, alignment; computational imaging; multi-view geometry; image features; video and event characterization; shape representation and recognition; stereo; reflectance, illumination, color; medical image analysis.

Reliable Face Recognition Methods

Author : Harry Wechsler
Publisher : Springer Science & Business Media
ISBN 13 : 0387384642
Total Pages : 332 pages
Book Rating : 4.3/5 (873 download)

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Book Synopsis Reliable Face Recognition Methods by : Harry Wechsler

Download or read book Reliable Face Recognition Methods written by Harry Wechsler and published by Springer Science & Business Media. This book was released on 2009-04-05 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book seeks to comprehensively address the face recognition problem while gaining new insights from complementary fields of endeavor. These include neurosciences, statistics, signal and image processing, computer vision, machine learning and data mining. The book examines the evolution of research surrounding the field to date, explores new directions, and offers specific guidance on the most promising venues for future research and development. The book’s focused approach and its clarity of presentation make this an excellent reference work.

Deep Learning-Based Face Analytics

Author : Nalini K Ratha
Publisher : Springer Nature
ISBN 13 : 3030746976
Total Pages : 405 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Deep Learning-Based Face Analytics by : Nalini K Ratha

Download or read book Deep Learning-Based Face Analytics written by Nalini K Ratha and published by Springer Nature. This book was released on 2021-08-16 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. 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. The prerequisites for optimal use are the basic knowledge of pattern recognition, machine learning, probability theory, and linear algebra.

Handbook of Face Recognition

Author : Stan Z. Li
Publisher : Springer Nature
ISBN 13 : 3031435672
Total Pages : 473 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis Handbook of Face Recognition by : Stan Z. Li

Download or read book Handbook of Face Recognition written by Stan Z. Li and published by Springer Nature. This book was released on 2024-01-30 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: The history of computer-aided face recognition dates to the 1960s, yet the problem of automatic face recognition – a task that humans perform routinely and effortlessly in our daily lives – still poses great challenges, especially in unconstrained conditions. This highly anticipated new edition provides a comprehensive account of face recognition research and technology, spanning the full range of topics needed for designing operational recognition systems. After a thorough introduction, each subsequent chapter focuses on a specific topic, reviewing background information, up-to-date techniques, and recent results, as well as offering challenges and future directions. Topics and features: Fully updated, revised, and expanded, covering the entire spectrum of concepts, methods, and algorithms for automated detection and recognition systems Provides comprehensive coverage of face detection, alignment, feature extraction, and recognition technologies, and issues in evaluation, systems, security, and applications Contains numerous step-by-step algorithms Describes a broad range of applications from person verification, surveillance, and security, to entertainment Presents contributions from an international selection of preeminent experts Integrates numerous supporting graphs, tables, charts, and performance data This practical and authoritative reference is an essential resource for researchers, professionals and students involved in image processing, computer vision, biometrics, security, Internet, mobile devices, human-computer interface, E-services, computer graphics and animation, and the computer game industry.

Unconstrained Face Recognition

Author : Shaohua Kevin Zhou
Publisher : Springer Science & Business Media
ISBN 13 : 0387294864
Total Pages : 244 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Unconstrained Face Recognition by : Shaohua Kevin Zhou

Download or read book Unconstrained Face Recognition written by Shaohua Kevin Zhou and published by Springer Science & Business Media. This book was released on 2006-10-11 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Learning with Kernels

Author : Bernhard Scholkopf
Publisher : MIT Press
ISBN 13 : 0262536579
Total Pages : 645 pages
Book Rating : 4.2/5 (625 download)

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Book Synopsis Learning with Kernels by : Bernhard Scholkopf

Download or read book Learning with Kernels written by Bernhard Scholkopf and published by MIT Press. This book was released on 2018-06-05 with total page 645 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to Support Vector Machines and related kernel methods. In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs—-kernels—for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tasks and domains by the choice of the kernel function and the base algorithm. They are replacing neural networks in a variety of fields, including engineering, information retrieval, and bioinformatics. Learning with Kernels provides an introduction to SVMs and related kernel methods. Although the book begins with the basics, it also includes the latest research. It provides all of the concepts necessary to enable a reader equipped with some basic mathematical knowledge to enter the world of machine learning using theoretically well-founded yet easy-to-use kernel algorithms and to understand and apply the powerful algorithms that have been developed over the last few years.

Face Recognition

Author : Miloš Oravec
Publisher : BoD – Books on Demand
ISBN 13 : 9533070609
Total Pages : 414 pages
Book Rating : 4.5/5 (33 download)

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Book Synopsis Face Recognition by : Miloš Oravec

Download or read book Face Recognition written by Miloš Oravec and published by BoD – Books on Demand. This book was released on 2010-04-01 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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).

Kernel Methods in Computer Vision

Author : Christoph H. Lampert
Publisher : Now Publishers Inc
ISBN 13 : 1601982682
Total Pages : 113 pages
Book Rating : 4.6/5 (19 download)

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Book Synopsis Kernel Methods in Computer Vision by : Christoph H. Lampert

Download or read book Kernel Methods in Computer Vision written by Christoph H. Lampert and published by Now Publishers Inc. This book was released on 2009 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: Few developments have influenced the field of computer vision in the last decade more than the introduction of statistical machine learning techniques. Particularly kernel-based classifiers, such as the support vector machine, have become indispensable tools, providing a unified framework for solving a wide range of image-related prediction tasks, including face recognition, object detection and action classification. By emphasizing the geometric intuition that all kernel methods rely on, Kernel Methods in Computer Vision provides an introduction to kernel-based machine learning techniques accessible to a wide audience including students, researchers and practitioners alike, without sacrificing mathematical correctness. It covers not only support vector machines but also less known techniques for kernel-based regression, outlier detection, clustering and dimensionality reduction. Additionally, it offers an outlook on recent developments in kernel methods that have not yet made it into the regular textbooks: structured prediction, dependency estimation and learning of the kernel function. Each topic is illustrated with examples of successful application in the computer vision literature, making Kernel Methods in Computer Vision a useful guide not only for those wanting to understand the working principles of kernel methods, but also for anyone wanting to apply them to real-life problems.

Face Detection and Recognition

Author : Asit Kumar Datta
Publisher : CRC Press
ISBN 13 : 148222657X
Total Pages : 353 pages
Book Rating : 4.4/5 (822 download)

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Book Synopsis Face Detection and Recognition by : Asit Kumar Datta

Download or read book Face Detection and Recognition written by Asit Kumar Datta and published by CRC Press. This book was released on 2015-10-28 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: Face detection and recognition are the nonintrusive biometrics of choice in many security applications. Examples of their use include border control, driver's license issuance, law enforcement investigations, and physical access control.Face Detection and Recognition: Theory and Practice elaborates on and explains the theory and practice of face de

Advances in Face Image Analysis

Author : Fadi Dornaika
Publisher : Bentham Science Publishers
ISBN 13 : 1681081105
Total Pages : 264 pages
Book Rating : 4.6/5 (81 download)

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Book Synopsis Advances in Face Image Analysis by : Fadi Dornaika

Download or read book Advances in Face Image Analysis written by Fadi Dornaika and published by Bentham Science Publishers. This book was released on 2016-03-02 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Face Image Analysis: Theory and applications describes several approaches to facial image analysis and recognition. Eleven chapters cover advances in computer vision and pattern recognition methods used to analyze facial data. The topics addressed in this book include automatic face detection, 3D face model fitting, robust face recognition, facial expression recognition, face image data embedding, model-less 3D face pose estimation and image-based age estimation. The chapters are also written by experts from a different research groups. Readers will, therefore, have access to contemporary knowledge on facial recognition with some diverse perspectives offered for individual techniques. The book is a useful resource for a wide audience such as i) researchers and professionals working in the field of face image analysis, ii) the entire pattern recognition community interested in processing and extracting features from raw face images, and iii) technical experts as well as postgraduate computer science students interested in cutting edge concepts of facial image recognition.

Neural Networks and Statistical Learning

Author : Ke-Lin Du
Publisher : Springer Nature
ISBN 13 : 1447174526
Total Pages : 988 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Neural Networks and Statistical Learning by : Ke-Lin Du

Download or read book Neural Networks and Statistical Learning written by Ke-Lin Du and published by Springer Nature. This book was released on 2019-09-12 with total page 988 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a broad yet detailed introduction to neural networks and machine learning in a statistical framework. A single, comprehensive resource for study and further research, it explores the major popular neural network models and statistical learning approaches with examples and exercises and allows readers to gain a practical working understanding of the content. This updated new edition presents recently published results and includes six new chapters that correspond to the recent advances in computational learning theory, sparse coding, deep learning, big data and cloud computing. Each chapter features state-of-the-art descriptions and significant research findings. The topics covered include: • multilayer perceptron; • the Hopfield network; • associative memory models;• clustering models and algorithms; • t he radial basis function network; • recurrent neural networks; • nonnegative matrix factorization; • independent component analysis; •probabilistic and Bayesian networks; and • fuzzy sets and logic. Focusing on the prominent accomplishments and their practical aspects, this book provides academic and technical staff, as well as graduate students and researchers with a solid foundation and comprehensive reference on the fields of neural networks, pattern recognition, signal processing, and machine learning.

Computational Science and Technology

Author : Rayner Alfred
Publisher : Springer
ISBN 13 : 9789811347979
Total Pages : 583 pages
Book Rating : 4.3/5 (479 download)

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Book Synopsis Computational Science and Technology by : Rayner Alfred

Download or read book Computational Science and Technology written by Rayner Alfred and published by Springer. This book was released on 2019-02-01 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features the proceedings of the Fifth International Conference on Computational Science and Technology 2018 (ICCST2018), held in Kota Kinabalu, Malaysia, on 29–30 August 2018. Of interest to practitioners and researchers, it presents exciting advances in computational techniques and solutions in this area. It also identifies emerging issues to help shape future research directions and enable industrial users to apply cutting-edge, large-scale and high-performance computational methods.

Pattern Recognition, Machine Intelligence and Biometrics

Author : Patrick S. P. Wang
Publisher : Springer Science & Business Media
ISBN 13 : 3642224075
Total Pages : 883 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Pattern Recognition, Machine Intelligence and Biometrics by : Patrick S. P. Wang

Download or read book Pattern Recognition, Machine Intelligence and Biometrics written by Patrick S. P. Wang and published by Springer Science & Business Media. This book was released on 2012-02-13 with total page 883 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Pattern Recognition, Machine Intelligence and Biometrics" covers the most recent developments in Pattern Recognition and its applications, using artificial intelligence technologies within an increasingly critical field. It covers topics such as: image analysis and fingerprint recognition; facial expressions and emotions; handwriting and signatures; iris recognition; hand-palm gestures; and multimodal based research. The applications span many fields, from engineering, scientific studies and experiments, to biomedical and diagnostic applications, to personal identification and homeland security. In addition, computer modeling and simulations of human behaviors are addressed in this collection of 31 chapters by top-ranked professionals from all over the world in the field of PR/AI/Biometrics. The book is intended for researchers and graduate students in Computer and Information Science, and in Communication and Control Engineering. Dr. Patrick S. P. Wang is a Professor Emeritus at the College of Computer and Information Science, Northeastern University, USA, Zijiang Chair of ECNU, Shanghai, and NSC Visiting Chair Professor of NTUST, Taipei.

Proceedings of the 12th National Technical Seminar on Unmanned System Technology 2020

Author : Khalid Isa
Publisher : Springer Nature
ISBN 13 : 9811624062
Total Pages : 1155 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Proceedings of the 12th National Technical Seminar on Unmanned System Technology 2020 by : Khalid Isa

Download or read book Proceedings of the 12th National Technical Seminar on Unmanned System Technology 2020 written by Khalid Isa and published by Springer Nature. This book was released on 2021-09-24 with total page 1155 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprises the proceedings of the 12th National Technical Symposium on Unmanned System Technology 2020 (NUSYS’20) held on October 27–28, 2020. It covers a number of topics, including intelligent robotics, novel sensor technology, control algorithms, acoustics signal processing, imaging techniques, biomimetic robots, green energy sources, and underwater communication backbones and protocols, and it appeals to researchers developing marine technology solutions and policy-makers interested in technologies to facilitate the exploration of coastal and oceanic regions.

Pattern Recognition with Support Vector Machines

Author : Seong-Whan Lee
Publisher : Springer
ISBN 13 : 3540456651
Total Pages : 428 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Pattern Recognition with Support Vector Machines by : Seong-Whan Lee

Download or read book Pattern Recognition with Support Vector Machines written by Seong-Whan Lee and published by Springer. This book was released on 2003-08-02 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First International Workshop on Pattern Recognition with Support Vector Machines, SVM 2002, held in Niagara Falls, Canada in August 2002.The 16 revised full papers and 14 poster papers presented together with two invited contributions were carefully reviewed and selected from 57 full paper submissions. The papers presented span the whole range of topics in pattern recognition with support vector machines from computational theories to implementations and applications.

Biometric Authentication

Author : Sun Yuan Kung
Publisher : Prentice Hall
ISBN 13 :
Total Pages : 504 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Biometric Authentication by : Sun Yuan Kung

Download or read book Biometric Authentication written by Sun Yuan Kung and published by Prentice Hall. This book was released on 2005 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: A breakthrough approach to improving biometrics performanceConstructing robust information processing systems for face and voice recognitionSupporting high-performance data fusion in multimodal systemsAlgorithms, implementation techniques, and application examples Machine learning: driving significant improvements in biometric performance As they improve, biometric authentication systems are becoming increasingly indispensable for protecting life and property. This book introduces powerful machine learning techniques that significantly improve biometric performance in a broad spectrum of application domains. Three leading researchers bridge the gap between research, design, and deployment, introducing key algorithms as well as practical implementation techniques. They demonstrate how to construct robust information processing systems for biometric authentication in both face and voice recognition systems, and to support data fusion in multimodal systems. Coverage includes: How machine learning approaches differ from conventional template matchingTheoretical pillars of machine learning for complex pattern recognition and classificationExpectation-maximization (EM) algorithms and support vector machines (SVM)Multi-layer learning models and back-propagation (BP) algorithmsProbabilistic decision-based neural networks (PDNNs) for face biometricsFlexible structural frameworks for incorporating machine learning subsystems in biometric applicationsHierarchical mixture of experts and inter-class learning strategies based on class-based modular networksMulti-cue data fusion techniques that integrate face and voice recognitionApplication case studies