Recognition of Humans and Their Activities Using Video (Synthesis Lectures in Image, Video, & Multimedia Processing)
Language: English
Published by Morgan & Claypool, 2005
- Softcover
- Used
Seller: BookOrders, Russell, IA, U.S.A.BookOrders
AbeBooks seller since October 4, 2000
Condition: Used - Very good
£ 15.56
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Add to basketItem description from seller
Ex-library with the usual features. Library label on front cover. The interior is clean and tight. Binding is good. Cover shows light wear.
Seller Inventory # 122062
- Title
- Recognition of Humans and Their Activities Using Video (Synthesis Lectures in Image, Video, & Multimedia Processing)
- Author
- Amit K. Roy-chowdhury; Rama Chellappa; Al Bovik; S. Kevin Zhou
- Publisher
- Morgan & Claypool
- Publication year
- 2005
- Condition
- Very Good
- Book Type
- Ex-Library
- Binding
- Soft Cover
- Language
- English
- ISBN 10
- 1598290061
- ISBN 13
- 9781598290066
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.
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