A Heat-Map-Based Algorithm for Recognizing Group Activities in Videos

In this paper, a new heat-map-based algorithm is proposed for group activity recognition. The proposed algorithm first models human trajectories as series of heat sources and then applies a thermal diffusion process to create a heat map (HM) for representing the group activities. Based on this HM, a...

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Published inIEEE transactions on circuits and systems for video technology Vol. 23; no. 11; pp. 1980 - 1992
Main Authors Lin, Weiyao, Chu, Hang, Wu, Jianxin, Sheng, Bin, Chen, Zhenzhong
Format Journal Article
LanguageEnglish
Published New York, NY IEEE 01.11.2013
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
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ISSN1051-8215
1558-2205
DOI10.1109/TCSVT.2013.2269780

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Abstract In this paper, a new heat-map-based algorithm is proposed for group activity recognition. The proposed algorithm first models human trajectories as series of heat sources and then applies a thermal diffusion process to create a heat map (HM) for representing the group activities. Based on this HM, a new key-point-based (KPB) method is used for handling the alignments among HMs with different scales and rotations. A surface-fitting (SF) method is also proposed for recognizing group activities. Our proposed HM feature can efficiently embed the temporal motion information of the group activities while the proposed KPB and SF methods can effectively utilize the characteristics of the HM for activity recognition. Section IV demonstrates the effectiveness of our proposed algorithms.
AbstractList In this paper, a new heat-map-based algorithm is proposed for group activity recognition. The proposed algorithm first models human trajectories as series of heat sources and then applies a thermal diffusion process to create a heat map (HM) for representing the group activities. Based on this HM, a new key-point-based (KPB) method is used for handling the alignments among HMs with different scales and rotations. A surface-fitting (SF) method is also proposed for recognizing group activities. Our proposed HM feature can efficiently embed the temporal motion information of the group activities while the proposed KPB and SF methods can effectively utilize the characteristics of the HM for activity recognition. Section IV demonstrates the effectiveness of our proposed algorithms.
Author Weiyao Lin
Bin Sheng
Zhenzhong Chen
Hang Chu
Jianxin Wu
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Issue 11
Keywords Performance evaluation
Thermal diffusion
heat map
Gesture recognition
Activity levels
group activity
Algorithm
Heat source
surface matching
Multiscale method
A posteriori estimation
Diffusion process
Activity recognition
Curve fitting
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SubjectTerms Activity recognition
Applied sciences
Diffusion processes
Exact sciences and technology
Feature extraction
group activity
heat map
Heating
Information, signal and communications theory
Pattern recognition
Signal processing
surface matching
Surface treatment
Telecommunications and information theory
Trajectory
Videos
Title A Heat-Map-Based Algorithm for Recognizing Group Activities in Videos
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