Please use this identifier to cite or link to this item: http://10.9.150.37:8080/dspace//handle/atmiyauni/996
Title: Implementation of Foreground Detection Algorithm Using Modified GMM for Outdoor Surveillance
Authors: Ghedia, Navneet
Vithalani, C.
Kothari, Ashish
Keywords: video surveillance and monitoring
Computer Vision
Background Model
Gaussian Mixture Model
Foreground Detection
Issue Date: Oct-2020
Publisher: GIS Science Journal
Citation: Ghedia, N. ,Vithalani, C. ,Kothari, A. (2020).Implementation of Foreground Detection Algorithm Using Modified GMM for Outdoor Surveillance. GIS Science Journal, 7(7), 634-641, ISSN NO : 1869-9391. DOI:20.18001.GSJ.2020.V7I7.20.35591
Abstract: Visual Monitoring System is the peak level research topic in Today’s era. Visual observation in computer vision helps to analyze object’s activities easily. Today’s era of computer vision will completely remove traditional human operated Video Surveillance System. A major part of smart video surveillance system is characterized by perception and the robustness of a Smart Video Surveillance System is not only to sense the environment, but also to interpret and act intelligently. Advancement in perception will lead to applications for defense and automated driving assistance. Nowadays researchers are working on object detection, object tracking, crowd analysis, pedestrian and vehicle identification to improve the security at the public places. The objective of the proposed work is to ensure high level of security in public places using static Pan Tilt Zoom (PTZ) camera and to develop robust object detection algorithm for the smart and vigilant video surveillance.
URI: http://10.9.150.37:8080/dspace//handle/atmiyauni/996
ISSN: 1869-9391
Appears in Collections:01. Journal Articles

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