Publication Type : Journal Article
Publisher : Advances in Intelligent Systems and Computing
Source : Advances in Intelligent Systems and Computing, Springer, Volume 320, p.117-124 (2015)
Url : https://link.springer.com/chapter/10.1007/978-3-319-11218-3_12
Keywords : Moving Region Extraction, Video surveillance, Visual Attention
Campus : Bengaluru
School : Department of Computer Science and Engineering, School of Engineering
Department : Computer Science
Year : 2015
Abstract : Visual Attention algorithms have been extensively used for object detection in images. However, the use of these algorithms for video analysis has been less explored. Many of the techniques proposed, though accurate and robust, still require a huge amount of time for processing large sized video data. Thus this paper introduces a fast and computationally inexpensive technique for detecting regions corresponding to moving humans in surveillance videos. It is based on the dynamic saliency model and is robust to noise and illumination variation. Results indicate successful extraction of moving human regions with minimum noise, and faster performance in comparison to other models. The model works best in sparsely crowded scenarios.
Cite this Research Publication : G. Sanjay, Amudha, J., and Jose, J. Tressa, “Moving Human Detection in Video Using Dynamic Visual Attention Model”, Advances in Intelligent Systems and Computing, vol. 320, pp. 117-124, 2015.