Paper
4 March 2015 Spatio-temporal action localization for human action recognition in large dataset
Sameh Megrhi, Marwa Jmal, Azeddine Beghdadi, Wided Mseddi
Author Affiliations +
Proceedings Volume 9407, Video Surveillance and Transportation Imaging Applications 2015; 94070O (2015) https://doi.org/10.1117/12.2082880
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States
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.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sameh Megrhi, Marwa Jmal, Azeddine Beghdadi, and 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); https://doi.org/10.1117/12.2082880
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Cited by 2 scholarly publications.
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KEYWORDS
Cameras

Video

Feature extraction

Image segmentation

Electroluminescent displays

Video processing

Image processing

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