Automated scene analysis has been a topic of great interest in computer vision and cognitive science. Recently, with the growth of crowd phenomena in the real world, crowded scene analysis has attracted much attention. However, the visual occlusions and ambiguities in crowded scenes, as well as the complex behaviors and scene semantics, make the analysis a challenging task. In the past few years, an increasing number of works on the crowded scene analysis have been reported, which covered different aspects including crowd motion pattern learning, crowd behavior and activity analyses, and anomaly detection in crowds. This paper surveys the state-of-the-art techniques on this topic. We first provide the background knowledge and the available features related to crowded scenes. Then, existing models, popular algorithms, evaluation protocols, and system performance are provided corresponding to different aspects of the crowded scene analysis. We also outline the available datasets for performance evaluation. Finally, some research problems and promising future directions are presented with discussions.
Crowded Scene Analysis: A Survey
Teng Li,Huan Chang,Meng Wang,Bingbing Ni,Richang Hong,Shuicheng Yan
Published 2015 in IEEE transactions on circuits and systems for video technology (Print)
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- Publication year
2015
- Venue
IEEE transactions on circuits and systems for video technology (Print)
- Publication date
2015-02-05
- Fields of study
Computer Science
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