Publication Type:

Conference Paper

Source:

Physics Procedia, Elsevier B.V., Volume 78, p.160-164 (2016)

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992389408&partnerID=40&md5=f861ed55b2751c66f7024aa05b280106

Keywords:

Background motion, Bottom up approach, Detection of moving object, Knowledge based systems, Monitoring, Motion analysis, Moving-object detection, Object Detection, Object recognition, Saliency detection, Security of data, Security systems, Surveillance video, Video Survelliance, Visual saliency

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. © 2016 The Authors.

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

Ra Aarthi, Amudha, Jb, Boomika, Ka, and Varrier, Aa, “Detection of Moving Objects in Surveillance Video by Integrating Bottom-up Approach with Knowledge Base”, in Physics Procedia, 2016, vol. 78, pp. 160-164.