Title

Understanding human behavior from motion imagery

Authors

Authors

M. Shah

Abbreviated Journal Title

Mach. Vis. Appl.

Keywords

video understanding; human behavior; representation; human activity; recognition; Computer Science, Artificial Intelligence; Computer Science, ; Cybernetics; Engineering, Electrical & Electronic

Abstract

Computer vision is gradually making the transition from image understanding to video understanding. This is due to the enormous success in analyzing sequences of images that has been achieved in recent years. The main shift in the paradigm has been from recognition followed by reconstruction (shape from X) to motion-based recognition. Since most videos are about people, this work has focused on the analysis of human motion. In this paper, I present my perspective on understanding human behavior. Automatically understanding human behavior from motion imagery involves extraction of relevant visual information from a video sequence, representation of that information in a suitable form, and interpretation of visual information for the purpose of recognition and learning about human behavior. Significant progress has been made in human tracking over the last few years. As compared with tracking, not much progress has been made in understanding human behavior, and the issue of representation has largely been ignored. I present my opinion on possible reasons and hurdles for slower progress in understanding human behavior, briefly present our work in tracking, representation, and recognition, and comment on the next steps in all three areas.

Journal Title

Machine Vision and Applications

Volume

14

Issue/Number

4

Publication Date

1-1-2003

Document Type

Article

Language

English

First Page

210

Last Page

214

WOS Identifier

WOS:000185702100005

ISSN

0932-8092

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