4 March 2015 Spatio-temporal action localization for human action recognition in large dataset
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Abstract
Human action recognition has drawn much attention in the field of video analysis. In this paper, we develop a human action detection and recognition process based on the tracking of Interest Points (IP) trajectory. A pre-processing step that performs spatio-temporal action detection is proposed. This step uses optical flow along with dense speed-up-robust-features (SURF) in order to detect and track moving humans in moving fields of view. The video description step is based on a fusion process that combines displacement and spatio-temporal descriptors. Experiments are carried out on the big data-set UCF-101. Experimental results reveal that the proposed techniques achieve better performances compared to many existing state-of-the-art action recognition approaches.
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Sameh Megrhi, Sameh Megrhi, Marwa Jmal, Marwa Jmal, Azeddine Beghdadi, Azeddine Beghdadi, Wided Mseddi, Wided Mseddi, "Spatio-temporal action localization for human action recognition in large dataset", Proc. SPIE 9407, Video Surveillance and Transportation Imaging Applications 2015, 94070O (4 March 2015); doi: 10.1117/12.2082880; https://doi.org/10.1117/12.2082880
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