Sciweavers

Share

Publication

Activity Understanding and Unusual Event Detection in Surveillance Videos

8 years 6 months ago
Activity Understanding and Unusual Event Detection in Surveillance Videos
Computer scientists have made ceaseless efforts to replicate cognitive video understanding abilities of human brains onto autonomous vision systems. As video surveillance cameras become ubiquitous, there is a surge in studies on automated activity understanding and unusual event detection in surveillance videos. Nevertheless, video content analysis in public scenes remained a formidable challenge due to intrinsic difficulties such as severe inter-object occlusion in crowded scene and poor quality of recorded surveillance footage. Moreover, it is nontrivial to achieve robust detection of unusual events, which are rare, ambiguous, and easily confused with noise. This thesis proposes solutions for resolving ambiguous visual observations and overcoming unreliability of conventional activity analysis methods by exploiting multi-camera visual context and human feedback.
Chen Change Loy
Added 11 Apr 2011
Updated 22 Sep 2011
Type Thesis
Year 2010
Authors Chen Change Loy
Comments (0)
books