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Proceedings Paper

CMA-HT: a crowd motion analysis framework based on heat-transfer analog model
Author(s): Yu Liang; William Melvin; Subramania I. Sritharan; Shane Fernandes; Darrell Barker
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Paper Abstract

Crowd motion analysis covers the detection, tracking, recognition, and behavior interpretation of target group from persistent surveillance video data. This project is dedicated to investigating a crowd motion analysis system based on a heat-transfer-analog model (denoted as CMA-HT for simplicity), and a generic modeling and simulation framework describing crowd motion behavior. CMA-HT is formulated by coupling the statistical analysis of crowd's historical behavior at a given location, geographic information system, and crowd motion dynamics. The mathematical derivation of the CMA-HT model and the innovative methods involved in the framework's implementation will be discussed in detail. Using the sample video data collected by Central Florida University as benchmark, CMA-HT is employed to measure and identify anomalous personnel or group responses in the video.

Paper Details

Date Published: 4 May 2012
PDF: 13 pages
Proc. SPIE 8402, Evolutionary and Bio-Inspired Computation: Theory and Applications VI, 84020J (4 May 2012); doi: 10.1117/12.919088
Show Author Affiliations
Yu Liang, Central State Univ. (United States)
William Melvin, Georgia Institute of Technology (United States)
Subramania I. Sritharan, Central State Univ. (United States)
Shane Fernandes, Central State Univ. (United States)
Darrell Barker, Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 8402:
Evolutionary and Bio-Inspired Computation: Theory and Applications VI
Olga Mendoza-Schrock; Mateen M. Rizki; Todd V. Rovito, Editor(s)

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