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Recognizing human-vehicle interactions from aerial video without training
2011
CVPR 2011 WORKSHOPS
We propose a novel framework to recognize humanvehicle interactions from aerial video. In this scenario, the object resolution is low, the visual cues are vague, and the detection and tracking of objects are less reliable as a consequence. Any methods that require the accurate tracking of objects or the exact matching of event definition are better avoided. To address these issues, we present a temporal logic based approach which does not require training from event examples. At the low-level,
doi:10.1109/cvprw.2011.5981794
dblp:conf/cvpr/LeeCA11
fatcat:2sebwvikvbaglmgkrw53nke2oq