Motion-Based Recognition
Motion-Based Recognition

Author: Mubarak Shah

Publisher: Springer Science & Business Media

Published: 2013-03-09

Total Pages: 378

ISBN-13: 9401589356

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Motion-based recognition deals with the recognition of an object and/or its motion, based on motion in a series of images. In this approach, a sequence containing a large number of frames is used to extract motion information. The advantage is that a longer sequence leads to recognition of higher level motions, like walking or running, which consist of a complex and coordinated series of events. Unlike much previous research in motion, this approach does not require explicit reconstruction of shape from the images prior to recognition. This book provides the state-of-the-art in this rapidly developing discipline. It consists of a collection of invited chapters by leading researchers in the world covering various aspects of motion-based recognition including lipreading, gesture recognition, facial expression recognition, gait analysis, cyclic motion detection, and activity recognition. Audience: This volume will be of interest to researchers and post- graduate students whose work involves computer vision, robotics and image processing.

Motion History Images for Action Recognition and Understanding
Motion History Images for Action Recognition and Understanding

Author: Md. Atiqur Rahman Ahad

Publisher: Springer Science & Business Media

Published: 2012-12-28

Total Pages: 132

ISBN-13: 1447147308

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Human action analysis and recognition is a relatively mature field, yet one which is often not well understood by students and researchers. The large number of possible variations in human motion and appearance, camera viewpoint, and environment, present considerable challenges. Some important and common problems remain unsolved by the computer vision community. However, many valuable approaches have been proposed over the past decade, including the motion history image (MHI) method. This method has received significant attention, as it offers greater robustness and performance than other techniques. This work presents a comprehensive review of these state-of-the-art approaches and their applications, with a particular focus on the MHI method and its variants.

Dynamic Vision for Perception and Control of Motion
Dynamic Vision for Perception and Control of Motion

Author: Ernst Dieter Dickmanns

Publisher: Springer Science & Business Media

Published: 2007-06-02

Total Pages: 490

ISBN-13: 1846286387

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This book on autonomous road-following vehicles brings together twenty years of innovation in the field. The book uniquely details an approach to real-time machine vision for the understanding of dynamic scenes, viewed from a moving platform that begins with spatio-temporal representations of motion for hypothesized objects whose parameters are adjusted by well-known prediction error feedback and recursive estimation techniques.

Image Understanding Workshop
Image Understanding Workshop

Author: United States. Defense Advanced Research Projects Agency. Information Science and Technology Office

Publisher:

Published: 1988

Total Pages: 534

ISBN-13:

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"The main theme of the 1988 workshop, the 18th in this DARPA sponsored series of meetings on Image Understanding and Computer Vision, is to cover new vision techniques in prototype vision systems for manufacturing, navigation, cartography, and photointerpretation." P. v.

View-Dependent Character Animation
View-Dependent Character Animation

Author: Parag Chaudhuri

Publisher: Springer Science & Business Media

Published: 2007-09-24

Total Pages: 149

ISBN-13: 1846287626

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Creating moving camera character animations in 3D is a multi-faceted computer graphics and computer vision problem that requires a formal representation of the moving camera, and efficient algorithms to help author manage and render the multitude of character poses required for the animation. This well-researched book introduces view-dependent character animation, covering all the relevant background work. Numerous example animations are offered to explain and illustrate this versatile technique.

Image Understanding
Image Understanding

Author: Yujin Zhang

Publisher: Walter de Gruyter GmbH & Co KG

Published: 2017-08-07

Total Pages: 312

ISBN-13: 3110524139

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This graduate textbook explains image reconstruction technologies based on region-based binocular and trinocular stereo vision, and object, pattern and relation matching. It further discusses principles and applications of multi-sensor fusion and content-based retrieval. Rich in examples and excises, the book concludes image engineering studies for electrical engineering and computer science students.

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

Author: José Ruiz-Shulcloper

Publisher: Springer

Published: 2013-11-04

Total Pages: 600

ISBN-13: 3642418279

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The two-volume set LNCS 8258 and 8259 constitutes the refereed proceedings of the 18th Iberoamerican Congress on Pattern Recognition, CIARP 2013, held in Havana, Cuba, in November 2013. The 137 papers presented, together with two keynotes, were carefully reviewed and selected from 262 submissions. The papers are organized in topical sections on mathematical theory of PR, supervised and unsupervised classification, feature or instance selection for classification, image analysis and retrieval, signals analysis and processing, applications of pattern recognition, biometrics, video analysis, and data mining.

Image Understanding in Unstructured Environment
Image Understanding in Unstructured Environment

Author: Su-shing Chen

Publisher: World Scientific

Published: 1988

Total Pages: 220

ISBN-13: 9789971504779

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In the development of autonomous sensory controlled systems, image understanding of sensory data is a difficult but important topic. Due to the unpredictable and uncertain nature of the environment, current image processing and computer vision approaches are not adequate to provide the capabilities needed by the systems. Thus, new approaches are required in the overall system design, including sophisticated reasoning processes, uncertainty management and adaptable architectures. This general issue is addressed by Thomas M Strat and Grahame B Smith. Lashon B Booker discusses the Bayesian approach in plausible reasoning for classification of complex ship images based on incomplete and uncertain evidence. Dynamic scene analysis is treated by Seetharaman Gunasekaran and Tzay Y Young. A spherical perspective approach is introduced to overcome some limitations of the current vision systems by Michael Penna and Su-shing Chen. Finally, Markov image models and their pixel-level approaches are extended to global approaches, through Dempster-Shafer and other techniques, by Mingchuan Zhang and Su-shing Chen.

Qualitative Motion Understanding
Qualitative Motion Understanding

Author: Wilhelm Burger

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 220

ISBN-13: 1461535662

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Mobile robots operating in real-world, outdoor scenarios depend on dynamic scene understanding for detecting and avoiding obstacles, recognizing landmarks, acquiring models, and for detecting and tracking moving objects. Motion understanding has been an active research effort for more than a decade, searching for solutions to some of these problems; however, it still remains one of the more difficult and challenging areas of computer vision research. Qualitative Motion Understanding describes a qualitative approach to dynamic scene and motion analysis, called DRIVE (Dynamic Reasoning from Integrated Visual Evidence). The DRIVE system addresses the problems of (a) estimating the robot's egomotion, (b) reconstructing the observed 3-D scene structure; and (c) evaluating the motion of individual objects from a sequence of monocular images. The approach is based on the FOE (focus of expansion) concept, but it takes a somewhat unconventional route. The DRIVE system uses a qualitative scene model and a fuzzy focus of expansion to estimate robot motion from visual cues, to detect and track moving objects, and to construct and maintain a global dynamic reference model.