Statistical Methods And Models For Video Based Tracking Modeling And Recognition
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Statistical Methods And Models For Video Based Tracking Modeling And Recognition
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Author : Rama Chellappa
language : en
Publisher: Now Publishers Inc
Release Date : 2010
Statistical Methods And Models For Video Based Tracking Modeling And Recognition written by Rama Chellappa and has been published by Now Publishers Inc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Computers categories.
Computer vision systems attempt to understand a scene and its components from mostly visual information. The geometry exhibited by the real world, the influence of material properties on scattering of incident light, and the process of imaging introduce constraints and properties that are key to solving some of these tasks. In the presence of noisy observations and other uncertainties, the algorithms make use of statistical methods for robust inference. In this paper, we highlight the role of geometric constraints in statistical estimation methods, and how the interplay of geometry and statistics leads to the choice and design of algorithms. In particular, we illustrate the role of imaging, illumination, and motion constraints in classical vision problems such as tracking, structure from motion, metrology, activity analysis and recognition, and appropriate statistical methods used in each of these problems.
Machine Learning For Vision Based Motion Analysis
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Author : Liang Wang
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-11-18
Machine Learning For Vision Based Motion Analysis written by Liang Wang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-18 with Computers categories.
Techniques of vision-based motion analysis aim to detect, track, identify, and generally understand the behavior of objects in image sequences. With the growth of video data in a wide range of applications from visual surveillance to human-machine interfaces, the ability to automatically analyze and understand object motions from video footage is of increasing importance. Among the latest developments in this field is the application of statistical machine learning algorithms for object tracking, activity modeling, and recognition. Developed from expert contributions to the first and second International Workshop on Machine Learning for Vision-Based Motion Analysis, this important text/reference highlights the latest algorithms and systems for robust and effective vision-based motion understanding from a machine learning perspective. Highlighting the benefits of collaboration between the communities of object motion understanding and machine learning, the book discusses the most active forefronts of research, including current challenges and potential future directions. Topics and features: provides a comprehensive review of the latest developments in vision-based motion analysis, presenting numerous case studies on state-of-the-art learning algorithms; examines algorithms for clustering and segmentation, and manifold learning for dynamical models; describes the theory behind mixed-state statistical models, with a focus on mixed-state Markov models that take into account spatial and temporal interaction; discusses object tracking in surveillance image streams, discriminative multiple target tracking, and guidewire tracking in fluoroscopy; explores issues of modeling for saliency detection, human gait modeling, modeling of extremely crowded scenes, and behavior modeling from video surveillance data; investigates methods for automatic recognition of gestures in Sign Language, and human action recognition from small training sets. Researchers, professional engineers, and graduate students in computer vision, pattern recognition and machine learning, will all find this text an accessible survey of machine learning techniques for vision-based motion analysis. The book will also be of interest to all who work with specific vision applications, such as surveillance, sport event analysis, healthcare, video conferencing, and motion video indexing and retrieval.
Statistical Learning And Pattern Analysis For Image And Video Processing
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Author : Nanning Zheng
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-07-25
Statistical Learning And Pattern Analysis For Image And Video Processing written by Nanning Zheng and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-07-25 with Computers categories.
Why are We Writing This Book? Visual data (graphical, image, video, and visualized data) affect every aspect of modern society. The cheap collection, storage, and transmission of vast amounts of visual data have revolutionized the practice of science, technology, and business. Innovations from various disciplines have been developed and applied to the task of designing intelligent machines that can automatically detect and exploit useful regularities (patterns) in visual data. One such approach to machine intelligence is statistical learning and pattern analysis for visual data. Over the past two decades, rapid advances have been made throughout the ?eld of visual pattern analysis. Some fundamental problems, including perceptual gro- ing,imagesegmentation, stereomatching, objectdetectionandrecognition,and- tion analysis and visual tracking, have become hot research topics and test beds in multiple areas of specialization, including mathematics, neuron-biometry, and c- nition. A great diversity of models and algorithms stemming from these disciplines has been proposed. To address the issues of ill-posed problems and uncertainties in visual pattern modeling and computing, researchers have developed rich toolkits based on pattern analysis theory, harmonic analysis and partial differential eq- tions, geometry and group theory, graph matching, and graph grammars. Among these technologies involved in intelligent visual information processing, statistical learning and pattern analysis is undoubtedly the most popular and imp- tant approach, and it is also one of the most rapidly developing ?elds, with many achievements in recent years. Above all, it provides a unifying theoretical fra- work for intelligent visual information processing applications.
Video Tracking
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Author : Emilio Maggio
language : en
Publisher: John Wiley & Sons
Release Date : 2011-07-05
Video Tracking written by Emilio Maggio and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-07-05 with Science categories.
Video Tracking provides a comprehensive treatment of the fundamental aspects of algorithm and application development for the task of estimating, over time, the position of objects of interest seen through cameras. Starting from the general problem definition and a review of existing and emerging video tracking applications, the book discusses popular methods, such as those based on correlation and gradient-descent. Using practical examples, the reader is introduced to the advantages and limitations of deterministic approaches, and is then guided toward more advanced video tracking solutions, such as those based on the Bayes’ recursive framework and on Random Finite Sets. Key features: Discusses the design choices and implementation issues required to turn the underlying mathematical models into a real-world effective tracking systems. Provides block diagrams and simil-code implementation of the algorithms. Reviews methods to evaluate the performance of video trackers – this is identified as a major problem by end-users. The book aims to help researchers and practitioners develop techniques and solutions based on the potential of video tracking applications. The design methodologies discussed throughout the book provide guidelines for developers in the industry working on vision-based applications. The book may also serve as a reference for engineering and computer science graduate students involved in vision, robotics, human-computer interaction, smart environments and virtual reality programmes
Statistical Methods In Video Processing
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Author : Dorin Comaniciu
language : en
Publisher: Springer Science & Business Media
Release Date : 2004-12-16
Statistical Methods In Video Processing written by Dorin Comaniciu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-12-16 with Computers categories.
The 2nd International Workshop on Statistical Methods in Video Processing, SMVP 2004, was held in Prague, Czech Republic, as an associated workshop of ECCV 2004, the 8th European Conference on Computer Vision. A total of 30 papers were submitted to the workshop. Of these, 17 papers were accepted for presentation and included in these proceedings, following a double-blind review process. The workshop had 42 registered participants. The focus of the meeting was on recent progress in the application of - vanced statistical methods to solve computer vision tasks. The one-day scienti?c program covered areas of high interest in vision research, such as dense rec- struction of 3D scenes, multibody motion segmentation, 3D shape inference, errors-in-variables estimation, probabilistic tracking, information fusion, optical ?owcomputation,learningfornonstationaryvideodata,noveltydetectionin- namic backgrounds, background modeling, grouping using feature uncertainty, and crowd segmentation from video. We wish to thank the authors of all submitted papers for their interest in the workshop.Wealsowishtothankthemembersofourprogramcommitteeandthe external reviewers for their commitment of time and e?ort in providing valuable recommendations for each submission. We are thankful to Vaclav Hlavac, the General Chair of ECCV 2004, and to Radim Sara, for the local organization of the workshop and registration management. We hope you will ?nd these proceedings both inspiring and of high scienti?c quality.
Computer Vision Accv 2007
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Author : Yasushi Yagi
language : en
Publisher: Springer
Release Date : 2007-11-14
Computer Vision Accv 2007 written by Yasushi Yagi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-11-14 with Computers categories.
This title is part of a two volume set that constitutes the refereed proceedings of the 8th Asian Conference on Computer Vision, ACCV 2007. Coverage includes shape and texture, image and video processing, face and gesture, tracking, camera networks, learning, motion and tracking, retrieval and search, human pose estimation, matching, face/gesture/action detection and recognition, low level vision and phtometory, motion and tracking, human detection, and segmentation.
Face Processing Advanced Modeling And Methods
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Author : Wenyi Zhao
language : en
Publisher: Elsevier
Release Date : 2011-07-28
Face Processing Advanced Modeling And Methods written by Wenyi Zhao and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-07-28 with Computers categories.
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
Background Modeling And Foreground Detection For Video Surveillance
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Author : Thierry Bouwmans
language : en
Publisher: CRC Press
Release Date : 2014-07-25
Background Modeling And Foreground Detection For Video Surveillance written by Thierry Bouwmans and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-25 with Computers categories.
Background modeling and foreground detection are important steps in video processing used to detect robustly moving objects in challenging environments. This requires effective methods for dealing with dynamic backgrounds and illumination changes as well as algorithms that must meet real-time and low memory requirements. Incorporating both established and new ideas, Background Modeling and Foreground Detection for Video Surveillance provides a complete overview of the concepts, algorithms, and applications related to background modeling and foreground detection. Leaders in the field address a wide range of challenges, including camera jitter and background subtraction. The book presents the top methods and algorithms for detecting moving objects in video surveillance. It covers statistical models, clustering models, neural networks, and fuzzy models. It also addresses sensors, hardware, and implementation issues and discusses the resources and datasets required for evaluating and comparing background subtraction algorithms. The datasets and codes used in the text, along with links to software demonstrations, are available on the book’s website. A one-stop resource on up-to-date models, algorithms, implementations, and benchmarking techniques, this book helps researchers and industry developers understand how to apply background models and foreground detection methods to video surveillance and related areas, such as optical motion capture, multimedia applications, teleconferencing, video editing, and human–computer interfaces. It can also be used in graduate courses on computer vision, image processing, real-time architecture, machine learning, or data mining.
Computer Vision Eccv 2008
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Author : David Forsyth
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-10-07
Computer Vision Eccv 2008 written by David Forsyth and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-10-07 with Computers categories.
The four-volume set comprising LNCS volumes 5302/5303/5304/5305 constitutes the refereed proceedings of the 10th European Conference on Computer Vision, ECCV 2008, held in Marseille, France, in October 2008. The 243 revised papers presented were carefully reviewed and selected from a total of 871 papers submitted. The four books cover the entire range of current issues in computer vision. The papers are organized in topical sections on recognition, stereo, people and face recognition, object tracking, matching, learning and features, MRFs, segmentation, computational photography and active reconstruction.
Statistical Model Based Video Segmentation And Its Application To Very Low Bit Rate Video Coding
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Author : International Business Machines Corporation. Research Division
language : en
Publisher:
Release Date : 1998
Statistical Model Based Video Segmentation And Its Application To Very Low Bit Rate Video Coding written by International Business Machines Corporation. Research Division and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Algorithms categories.
Abstract: "We present a statistical model-based video segmentation algorithm for typical videophone and videoconference applications. This algorithm makes use of online information and tries to build statistical models for both background and foreground and update the models on the fly. A hierarchical system structure is designed and segmentation is combined with tracking. Two possible applications are discussed: to generate VOP for MPEG-4 and to introduce subjective rate control for DCT-based algorithms. A R-D based rate control algorithm for H.263 is proposed and implemented as an example."