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24 May 2012 Automatic human action recognition in a scene from visual inputs
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Abstract
Surveillance is normally performed by humans, since it requires visual intelligence. However, this can be dull and dangerous, especially for military operations. Therefore, unmanned autonomous visual-intelligence systems are desired. In this paper, we present a novel system that can recognize human actions, which are relevant to detect operationally significant activity. Central to the system is a break-down of high-level perceptual concepts (verbs) in simpler observable events. The system is trained on 3482 videos and evaluated on 2589 videos from the DARPA Mind's Eye program, with for each video human annotations indicating the presence or absence of 48 different actions. The results show that our system reaches good performance approaching the human average response.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Henri Bouma, Patrick Hanckmann, Jan-Willem Marck, Leo Penning, Richard den Hollander, Johan-Martijn ten Hove, Sebastiaan van den Broek, Klamer Schutte, and Gertjan Burghouts "Automatic human action recognition in a scene from visual inputs", Proc. SPIE 8388, Unattended Ground, Sea, and Air Sensor Technologies and Applications XIV, 83880L (24 May 2012); https://doi.org/10.1117/12.918582
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