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Real-time human action recognition by luminance field trajectory analysis
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International Multimedia Conference archive
Proceeding of the 16th ACM international conference on Multimedia table of contents
Vancouver, British Columbia, Canada
SESSION: Content track short papers session 1: content analysis table of contents
Pages 671-676  
Year of Publication: 2008
ISBN:978-1-60558-303-7
Authors
Zhu Li  Hong Kong Polytechnic University, Kowloon, Hong Kong
Yun Fu  University of Illinois, Urbana-Champaign, IL, USA
Thomas Huang  University of Illinois, Urbana-Champaign, IL, USA
Shuicheng Yan  National University of Singapore, Singapore, Singapore
Sponsors
ACM: Association for Computing Machinery
SIGMULTIMEDIA: ACM Special Interest Group on Multimedia
Publisher
ACM  New York, NY, USA
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ABSTRACT

The explosive growth of video content in recent years fueled by the technological leaps in computing and communication has created new challenges for video content analysis that can serve applications in video surveillance, video searching and mining. Human action detection and recognition is one of the important tasks in this effort. In this paper, we present a luminance field manifold trajectory analysis based solution for human activity recognition, without explicit object level information extraction and understanding. This approach is computationally efficient and can operate in real time. The recognition performance is also comparable with the state of art in comparable set ups.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Zhu Li: colleagues
Yun Fu: colleagues
Thomas Huang: colleagues
Shuicheng Yan: colleagues