Stochastic Algorithms for Visual Tracking
Stochastic Algorithms for Visual Tracking

Author: John MacCormick

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 184

ISBN-13: 1447106792

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A central problem in computer vision is to track objects as they move and deform in a video sequence. Stochastic algorithms -- in particular, particle filters and the Condensation algorithm -- have dramatically enhanced the state of the art for such visual tracking problems in recent years. This book presents a unified framework for visual tracking using particle filters, including the new technique of partitioned sampling which can alleviate the "curse of dimensionality" suffered by standard particle filters. The book also introduces the notion of contour likelihood: a collection of models for assessing object shape, colour and motion, which are derived from the statistical properties of image features. Because of their statistical nature, contour likelihoods are ideal for use in stochastic algorithms. A unifying theme of the book is the use of statistics and probability, which enable the final output of the algorithms presented to be interpreted as the computer's "belief" about the state of the world. The book will be of use and interest to students, researchers and practitioners in computer vision, and assumes only an elementary knowledge of probability theory.

Video Tracking
Video Tracking

Author: Emilio Maggio

Publisher: John Wiley & Sons

Published: 2011-07-05

Total Pages: 308

ISBN-13: 1119956862

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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

Articulated Motion and Deformable Objects
Articulated Motion and Deformable Objects

Author: Francisco J. Perales

Publisher: Springer

Published: 2004-08-20

Total Pages: 282

ISBN-13: 3540300740

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The AMDO 2004 workshop took place at the Universitat de les Illes Balears (UIB) on 22-24 September, 2004, institutionally sponsored by the International Association for Pattern Recognition (IAPR), the MCYT (Comision Interm- isterial de Ciencia y Tecnologia, Spanish Government), the AERFAI (Spanish Association for Pattern Recognition and Image Analysis), the EG (Eurogra- ics Association) and the Mathematics and Computer Science Department of the UIB. Also important commercial sponsors collaborated with practical dem- strations; the main contributors were: Barco Electronics Systems (Title Sp- sor), VICOM Tech, ANDROME Iberica, CESA and TAGrv. The subject of the workshop was ongoing research in articulated motion on a sequence of images and sophisticated models for deformable objects. The goals of these areas are to understand and interpret the motion of complex objects that can be found in sequences of images in the real world. The main topics considered priorities are: deformable models, motion analysis, articulated models and animation, visualization of deformable models, 3D recovery from motion, single or multiple human motion analysis and synthesis, applications of deformable models and motion analysis, face tracking, recovery and recognition models, and virtual and augmented reality systems.

Gesture in Human-Computer Interaction and Simulation
Gesture in Human-Computer Interaction and Simulation

Author: Sylvie Gibet

Publisher: Springer

Published: 2006-02-15

Total Pages: 356

ISBN-13: 3540326251

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This book constitutes the thoroughly refereed post-proceedings of the 6th International Workshop on Gesture in Human-Computer Interaction and Simulation, GW 2005, held in May 2005. The 22 revised long papers and 14 revised short papers presented together with 2 invited lectures were carefully selected from numerous submissions during two rounds of reviewing and improvement. The papers are organized in topical sections on human perception and production of gesture, sign language representation, sign language recognition, vision-based gesture recognition, gesture analysis, gesture synthesis, gesture and music, and gesture interaction in multimodal systems.

Audio-visual Person Tracking: A Practical Approach
Audio-visual Person Tracking: A Practical Approach

Author: Fotios Talantzis

Publisher: World Scientific

Published: 2011-12-23

Total Pages: 234

ISBN-13: 1848169493

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This book deals with the creation of the algorithmic backbone that enables a computer to perceive humans in a monitored space. This is performed using the same signals that humans process, i.e., audio and video. Computers reproduce the same type of perception using sensors and algorithms in order to detect and track multiple interacting humans, by way of multiple cues, like bodies, faces or speech. This application domain is challenging, because audio and visual signals are cluttered by both background and foreground objects. First, particle filtering is established as the framework for tracking. Then, audio, visual and also audio-visual tracking systems are separately explained. Each modality is analyzed, starting with sensor configuration, detection for tracker initialization and the trackers themselves. Techniques to fuse the modalities are then considered. Instead of offering a monolithic approach to the tracking problem, this book also focuses on implementation by providing MATLAB code for every presented component. This way, the reader can connect every concept with corresponding code. Finally, the applications of the various tracking systems in different domains are studied./a

Advanced Concepts for Intelligent Vision Systems
Advanced Concepts for Intelligent Vision Systems

Author: Jaques Blanc-Talon

Publisher: Springer

Published: 2011-09-06

Total Pages: 777

ISBN-13: 3642236871

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This book constitutes the refereed proceedings of the 13th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2011, held in Ghent, Belgium, in August 2011. The 66 revised full papers presented were carefully reviewed and selected from 124 submissions. The papers are organized in topical sections on classification recognition, and tracking, segmentation, images analysis, image processing, video surveillance and biometrics, algorithms and optimization; and 3D, depth and scene understanding.

Digital Image Computing: Techniques and Applications
Digital Image Computing: Techniques and Applications

Author: Changming Sun

Publisher: CSIRO PUBLISHING

Published: 2003-12-01

Total Pages: 916

ISBN-13: 0643098836

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Digital Image Computing: Techniques and Applications is the premier biennial conference in Australia on the topics of image processing and image analysis. This seventh edition of the proceedings has seen an unprecedented level of submission, on such diverse areas as: Image processing; Face recognition; Segmentation; Registration; Motion analysis; Medical imaging; Object recognition; Virtual environments; Graphics; Stereo-vision; and Video analysis. These two volumes contain all the 108 accepted papers and five invited talks that were presented at the conference. These two volumes provide the Australian and international imaging research community with a snapshot of current theoretical and practical developments in these areas. They are of value to any engineer, computer scientist, mathematician, statistician or student interested in these matters.

Recent Advances in AI-enabled Automated Medical Diagnosis
Recent Advances in AI-enabled Automated Medical Diagnosis

Author: Richard Jiang

Publisher: CRC Press

Published: 2022-10-20

Total Pages: 371

ISBN-13: 1000781208

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Developments in deep learning in the past decade have led to phenomenal growth in AI-based automated medical diagnosis, opening a door to a new era of both medical research and medical industry. It is a golden age for researchers involved in the development and application of advanced machine learning techniques for medical and clinical problems. This book captures the most recent important advances in this cross-disciplinary topic and brings the latest advances to a wide audience including experts, researchers, students, industry developers and medical services.

Metaheuristics for Dynamic Optimization
Metaheuristics for Dynamic Optimization

Author: Enrique Alba

Publisher: Springer

Published: 2012-08-11

Total Pages: 417

ISBN-13: 3642306659

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This book is an updated effort in summarizing the trending topics and new hot research lines in solving dynamic problems using metaheuristics. An analysis of the present state in solving complex problems quickly draws a clear picture: problems that change in time, having noise and uncertainties in their definition are becoming very important. The tools to face these problems are still to be built, since existing techniques are either slow or inefficient in tracking the many global optima that those problems are presenting to the solver technique. Thus, this book is devoted to include several of the most important advances in solving dynamic problems. Metaheuristics are the more popular tools to this end, and then we can find in the book how to best use genetic algorithms, particle swarm, ant colonies, immune systems, variable neighborhood search, and many other bioinspired techniques. Also, neural network solutions are considered in this book. Both, theory and practice have been addressed in the chapters of the book. Mathematical background and methodological tools in solving this new class of problems and applications are included. From the applications point of view, not just academic benchmarks are dealt with, but also real world applications in logistics and bioinformatics are discussed here. The book then covers theory and practice, as well as discrete versus continuous dynamic optimization, in the aim of creating a fresh and comprehensive volume. This book is targeted to either beginners and experienced practitioners in dynamic optimization, since we took care of devising the chapters in a way that a wide audience could profit from its contents. We hope to offer a single source for up-to-date information in dynamic optimization, an inspiring and attractive new research domain that appeared in these last years and is here to stay.

Unconstrained Face Recognition
Unconstrained Face Recognition

Author: Shaohua Kevin Zhou

Publisher: Springer Science & Business Media

Published: 2006-10-11

Total Pages: 244

ISBN-13: 0387294864

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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.