Understanding human behavior from motion imagery

    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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