Publication Type:

Journal Article

Source:

Procedia Computer Science, Volume 78, p.160 - 164 (2016)

URL:

http://www.sciencedirect.com/science/article/pii/S1877050916000284

Keywords:

Video Survelliance; Visual Saliency; Moving Object Detection

Abstract:

Abstract In the modern age, where every prominent and populous area of a city is continuously monitored, a lot of data in the form of video has to be analyzed. There is a need for an algorithm that helps in the demarcation of the abnormal activities, for ensuring better security. To decrease perceptual overload in \{CCTV\} monitoring, automation of focusing the attention on significant events happening in overpopulated public scenes is also necessary. The major challenge lies in differentiating detecting of salient motion and background motion. This paper discusses a saliency detection method that aims to discover and localize the moving regions for indoor and outdoor surveillance videos. This method does not require any prior knowledge of a scene and this has been verified with snippets of surveillance footages.

Notes:

cited By 0; Conference of 1st International Conference on Information Security and Privacy 2015 ; Conference Date: 11 December 2015 Through 12 December 2015; Conference Code:131692

Cite this Research Publication

A. R., Amudha, J., K., B., and Varrier, A., “Detection of Moving Objects in Surveillance Video by Integrating Bottom-up Approach with Knowledge Base”, Procedia Computer Science, vol. 78, pp. 160 - 164, 2016.

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