Improved Intelligence Surveillance System for Object Detection, Classification of Human Behaviour using GMM and Open CV
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 112 | Views: 373

Research Paper | Computer Science & Engineering | India | Volume 4 Issue 1, January 2015 | Popularity: 6.8 / 10


     

Improved Intelligence Surveillance System for Object Detection, Classification of Human Behaviour using GMM and Open CV

Rajkumar Bhimrao Pawar, Praveen R. Barapatre


Abstract: Real object motion detection has widely used in surveillance system such as intelligent security systems, airport security systems, video monitoring systems, etc. Object tracking is one of the most necessary steps for surveillance system. Moving object and background separation must be separated as much as clear. Motion detection is nothing but movement of objects. This pre processing can be done with the help of various techniques like GMM. A popular object segmentation strategy is background subtraction. While traditional methods of Segmentation using Thresholding, Background subtraction and Background estimation provide satisfactory results to detect single objects, noise is produced in case of multiple objects and in poor lighting conditions. In this paper we will be focusing on important features to build an advanced intelligent surveillance system and its architecture. To reduce the crime rate in any country advanced intelligent surveillance system required to automatically detect the illegal activities done by any criminal.


Keywords: GMM, Surveillance, Thresholding, CCTV, Segmentation, Loitering


Edition: Volume 4 Issue 1, January 2015


Pages: 2613 - 2617



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Rajkumar Bhimrao Pawar, Praveen R. Barapatre, "Improved Intelligence Surveillance System for Object Detection, Classification of Human Behaviour using GMM and Open CV ", International Journal of Science and Research (IJSR), Volume 4 Issue 1, January 2015, pp. 2613-2617, https://www.ijsr.net/getabstract.php?paperid=SUB15892, DOI: https://www.doi.org/10.21275/SUB15892

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