Recognition of humans and their activities using video
By: Chellappa, Rama.
Contributor(s): Roy-Chowdhury, Amit K | Zhou, S. Kevin.
Material type:
BookSeries: Synthesis lectures on image, video, and multimedia processing: #1.Publisher: San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool Publishers, c2005Edition: 1st ed.Description: 1 electronic document (ix, 173 p.) : digital file.ISBN: 1598290061 (electronic bk.); 9781598290066 (electronic bk.).Uniform titles: Synthesis digital library of engineering and computer science. Subject(s): Biometric identification | Gait in humans | Human face recognition (Computer science) | Image analysis | Image processing -- Digital techniques | Pattern recognition | Face recognition | Gait recognition | Human activity recognitionDDC classification: 006.4 Online resources: Abstract with links to resource | Abstract with links to full text | Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
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E books
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PK Kelkar Library, IIT Kanpur | Available | EBKE078 |
Mode of access: World Wide Web.
System requirements: PDF reader.
Part of: Synthesis digital library of engineering and computer science.
Series from website.
Series statement from caption on home page.
Includes bibliographical references (p. 153-170).
Introduction -- Human recognition using face -- Human recognition using gait -- Human activity recognition -- Future research directions -- Conclusions -- References.
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INSPEC
The recognition of humans and their activities from video sequences is currently a very active area of research because of its applications in video surveillance, design of realistic entertainment systems, multimedia communications, and medical diagnosis. In this lecture, we discuss the use of face and gait signatures for human identification and recognition of human activities from video sequences. We survey existing work and describe some of the more well-known methods in these areas. We also describe our own research and outline future possibilities. In the area of face recognition, we start with the traditional methods for image-based analysis and then describe some of the more recent developments related to the use of video sequences, 3D models, and techniques for representing variations of illumination. We note that the main challenge facing researchers in this area is the development of recognition strategies that are robust to changes due to pose, illumination, disguise, and aging. Gait recognition is a more recent area of research in video understanding, although it has been studied for a long time in psychophysics and kinesiology. The goal for video scientists working in this area is to automatically extract the parameters for representation of human gait. We describe some of the techniques that have been developed for this purpose, most of which are appearance based. We also highlight the challenges involved in dealing with changes in viewpoint and propose methods based on image synthesis, visual hull, and 3D models. In the domain of human activity recognition, we present an extensive survey of various methods that have been developed in different disciplines like artificial intelligence, image processing, pattern recognition, and computer vision. We then outline our method for modeling complex activities using 2D and 3D deformable shape theory. The wide application of automatic human identification and activity recognition methods will require the fusion of different modalities like face and gait, dealing with the problems of pose and illumination variations, and accurate computation of 3D models. The last chapter of this lecture deals with these areas of future research.
Title from PDF t.p. (viewed on Oct. 10, 2008).
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