Low Rank And Sparse Modeling For Visual Analysis

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Low Rank And Sparse Modeling For Visual Analysis

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Author : Yun Fu
language : en
Publisher: Springer
Release Date : 2014-11-01

Low Rank And Sparse Modeling For Visual Analysis written by Yun Fu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-01 with Computers categories.

This book provides a view of low-rank and sparse computing, especially approximation, recovery, representation, scaling, coding, embedding and learning among unconstrained visual data. The book includes chapters covering multiple emerging topics in this new field. It links multiple popular research fields in Human-Centered Computing, Social Media, Image Classification, Pattern Recognition, Computer Vision, Big Data, and Human-Computer Interaction. Contains an overview of the low-rank and sparse modeling techniques for visual analysis by examining both theoretical analysis and real-world applications.

Low Rank And Sparse Modeling For Visual Analysis

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Author : Yun Fu
language : en
Publisher: Springer
Release Date : 2014-10-30

Low Rank And Sparse Modeling For Visual Analysis written by Yun Fu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-30 with Computers categories.

This book provides a view of low-rank and sparse computing, especially approximation, recovery, representation, scaling, coding, embedding and learning among unconstrained visual data. The book includes chapters covering multiple emerging topics in this new field. It links multiple popular research fields in Human-Centered Computing, Social Media, Image Classification, Pattern Recognition, Computer Vision, Big Data, and Human-Computer Interaction. Contains an overview of the low-rank and sparse modeling techniques for visual analysis by examining both theoretical analysis and real-world applications.

Low Rank Models In Visual Analysis

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Author : Zhouchen Lin
language : en
Publisher: Academic Press
Release Date : 2017-06-06

Low Rank Models In Visual Analysis written by Zhouchen Lin and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-06 with Computers categories.

Low-Rank Models in Visual Analysis: Theories, Algorithms, and Applications presents the state-of-the-art on low-rank models and their application to visual analysis. It provides insight into the ideas behind the models and their algorithms, giving details of their formulation and deduction. The main applications included are video denoising, background modeling, image alignment and rectification, motion segmentation, image segmentation and image saliency detection. Readers will learn which Low-rank models are highly useful in practice (both linear and nonlinear models), how to solve low-rank models efficiently, and how to apply low-rank models to real problems. - Presents a self-contained, up-to-date introduction that covers underlying theory, algorithms and the state-of-the-art in current applications - Provides a full and clear explanation of the theory behind the models - Includes detailed proofs in the appendices

Low Rank Approximation

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Author : Ivan Markovsky
language : en
Publisher: Springer
Release Date : 2018-08-03

Low Rank Approximation written by Ivan Markovsky and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-03 with Technology & Engineering categories.

This book is a comprehensive exposition of the theory, algorithms, and applications of structured low-rank approximation. Local optimization methods and effective suboptimal convex relaxations for Toeplitz, Hankel, and Sylvester structured problems are presented. A major part of the text is devoted to application of the theory with a range of applications from systems and control theory to psychometrics being described. Special knowledge of the application fields is not required. The second edition of /Low-Rank Approximation/ is a thoroughly edited and extensively rewritten revision. It contains new chapters and sections that introduce the topics of: • variable projection for structured low-rank approximation;• missing data estimation;• data-driven filtering and control;• stochastic model representation and identification;• identification of polynomial time-invariant systems; and• blind identification with deterministic input model. The book is complemented by a software implementation of the methods presented, which makes the theory directly applicable in practice. In particular, all numerical examples in the book are included in demonstration files and can be reproduced by the reader. This gives hands-on experience with the theory and methods detailed. In addition, exercises and MATLAB^® /Octave examples will assist the reader quickly to assimilate the theory on a chapter-by-chapter basis. “Each chapter is completed with a new section of exercises to which complete solutions are provided.” Low-Rank Approximation (second edition) is a broad survey of the Low-Rank Approximation theory and applications of its field which will be of direct interest to researchers in system identification, control and systems theory, numerical linear algebra and optimization. The supplementary problems and solutions render it suitable for use in teaching graduate courses in those subjects as well.

Anomaly Detection In Video Surveillance

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Author : Xiaochun Wang
language : en
Publisher: Springer Nature
Release Date : 2024-08-06

Anomaly Detection In Video Surveillance written by Xiaochun Wang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-06 with Computers categories.

Anomaly detection in video surveillance stands at the core of numerous real-world applications that have broad impact and generate significant academic and industrial value. The key advantage of writing the book at this point in time is that the vast amount of work done by computer scientists over the last few decades has remained largely untouched by a formal book on the subject, although these techniques significantly advance existing methods of image and video analysis and understanding by taking advantage of anomaly detection in the data mining community and visual analysis in the computer vision community. The proposed book provides a comprehensive coverage of the advances in video based anomaly detection, including topics such as the theories of anomaly detection and machine perception for the functional analysis of abnormal events in general, the identification of abnormal behaviour and crowd abnormal behaviour in particular, the current understanding of computer vision development, and the application of this present understanding towards improving video-based anomaly detection in theory and coding with OpenCV. The book also provides a perspective on deep learning on human action recognition and behaviour analysis, laying the groundwork for future advances in these areas. Overall, the chapters of this book have been carefully organized with extensive bibliographic notes attached to each chapter. One of the goals is to provide the first systematic and comprehensive description of the range of data-driven solutions currently being developed up to date for such purposes. Another is to serve a dual purpose so that students and practitioners can use it as a textbook while researchers can use it as a reference book. A final goal is to provide a comprehensive exposition of the topic of anomaly detection in video media from multiple points of view.

High Dimensional And Low Quality Visual Information Processing

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Author : Yue Deng
language : en
Publisher: Springer
Release Date : 2014-09-04

High Dimensional And Low Quality Visual Information Processing written by Yue Deng and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-04 with Technology & Engineering categories.

This thesis primarily focuses on how to carry out intelligent sensing and understand the high-dimensional and low-quality visual information. After exploring the inherent structures of the visual data, it proposes a number of computational models covering an extensive range of mathematical topics, including compressive sensing, graph theory, probabilistic learning and information theory. These computational models are also applied to address a number of real-world problems including biometric recognition, stereo signal reconstruction, natural scene parsing, and SAR image processing.

Intelligent Data Engineering And Analytics

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Author : Vikrant Bhateja
language : en
Publisher: Springer Nature
Release Date : 2023-02-23

Intelligent Data Engineering And Analytics written by Vikrant Bhateja and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-23 with Technology & Engineering categories.

The book presents the proceedings of the 10th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2022), held at NIT Mizoram, Aizawl, Mizoram, India during 18 – 19 June 2022. Researchers, scientists, engineers, and practitioners exchange new ideas and experiences in the domain of intelligent computing theories with prospective applications in various engineering disciplines in the book. These proceedings are divided into two volumes. It covers broad areas of information and decision sciences, with papers exploring both the theoretical and practical aspects of data-intensive computing, data mining, evolutionary computation, knowledge management and networks, sensor networks, signal processing, wireless networks, protocols and architectures. This volume is a valuable resource for postgraduate students in various engineering disciplines.

Vision Models For High Dynamic Range And Wide Colour Gamut Imaging

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Author : Marcelo Bertalmío
language : en
Publisher: Academic Press
Release Date : 2019-11-06

Vision Models For High Dynamic Range And Wide Colour Gamut Imaging written by Marcelo Bertalmío and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-06 with Computers categories.

To enhance the overall viewing experience (for cinema, TV, games, AR/VR) the media industry is continuously striving to improve image quality. Currently the emphasis is on High Dynamic Range (HDR) and Wide Colour Gamut (WCG) technologies, which yield images with greater contrast and more vivid colours. The uptake of these technologies, however, has been hampered by the significant challenge of understanding the science behind visual perception. Vision Models for High Dynamic Range and Wide Colour Gamut Imaging provides university researchers and graduate students in computer science, computer engineering, vision science, as well as industry R&D engineers, an insight into the science and methods for HDR and WCG. It presents the underlying principles and latest practical methods in a detailed and accessible way, highlighting how the use of vision models is a key element of all state-of-the-art methods for these emerging technologies. - Presents the underlying vision science principles and models that are essential to the emerging technologies of HDR and WCG - Explores state-of-the-art techniques for tone and gamut mapping - Discusses open challenges and future directions of HDR and WCG research

Intelligence Science And Big Data Engineering Visual Data Engineering

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Author : Zhen Cui
language : en
Publisher: Springer Nature
Release Date : 2019-11-28

Intelligence Science And Big Data Engineering Visual Data Engineering written by Zhen Cui and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-28 with Computers categories.

The two volumes LNCS 11935 and 11936 constitute the proceedings of the 9th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2019, held in Nanjing, China, in October 2019. The 84 full papers presented were carefully reviewed and selected from 252 submissions.The papers are organized in two parts: visual data engineering; and big data and machine learning. They cover a large range of topics including information theoretic and Bayesian approaches, probabilistic graphical models, big data analysis, neural networks and neuro-informatics, bioinformatics, computational biology and brain-computer interfaces, as well as advances in fundamental pattern recognition techniques relevant to image processing, computer vision and machine learning.

Sparse Modeling For Image And Vision Processing

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Author : Julien Mairal
language : en
Publisher: Now Publishers
Release Date : 2014-12-19

Sparse Modeling For Image And Vision Processing written by Julien Mairal and has been published by Now Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-19 with Computers categories.

Sparse Modeling for Image and Vision Processing offers a self-contained view of sparse modeling for visual recognition and image processing. More specifically, it focuses on applications where the dictionary is learned and adapted to data, yielding a compact representation that has been successful in various contexts.