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 |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
761) 12966_Ashish Mahendrabhai Kothari.pdf | 306.12 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.