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A large-scale benchmark dataset for event recognition in surveillance video
2011
CVPR 2011
We introduce a new large-scale video dataset designed to assess the performance of diverse visual event recognition algorithms with a focus on continuous visual event recognition (CVER) in outdoor areas with wide coverage. Previous datasets for action recognition are unrealistic for real-world surveillance because they consist of short clips showing one action by one individual [15, 8] . Datasets have been developed for movies [11] and sports [12] , but, these actions and scene conditions do
doi:10.1109/cvpr.2011.5995586
dblp:conf/cvpr/OhHPCCLMALDSWJRSVPRYTSFRD11
fatcat:fkkxv762izfetdrthrhnopjbb4