• Dr. Navneet S. Ghedia
• Dr. C. H. Vithalani
• Dr. Ashish Kothari
• Dr. Chiragkumar N. Jasani

To ensure the high-level safety measures at a communal place one must have to approximation the background model and foreground detection in video scene under different constraints. To detect and track the moving objects (human, vehicle, animal, etc)in a video or real time investigation must responsive about the interface amongst the motion objects, their abnormal motion in existence of the stationary or dynamic background. This paper exhibits the definitive solution to the problem of the visual monitoring in outdoor environment. To accomplish the objective of the paper we represent foreground and the background by means of the statistical approach. Approximate the background model in such a way that it can unable to handle the picture sensitivity and also deals with the other variation like abrupt motion, illumination variation and occlusions. Foreground can be easily estimated with the help of foreground mask and then the target object is being tracked with the recursive filtering approach. The proposed Gaussian based detection and tracking approach is implemented with MATLAB. The experimental result and performance evaluation shows the robustness of the proposed Gaussian base approach. The proposed approach is experimentally tested with standard datasets.

Background Estimation, Video Surveillance,Foreground Detection, Object Tracking.

"Outdoor Motion Surveillance: Modified GMM and Kalman", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.377-383, May-2019, Available :http://www.jetir.org/papers/JETIR1905Y54.pdf

"Outdoor Motion Surveillance: Modified GMM and Kalman", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp377-383, May-2019, Available at : http://www.jetir.org/papers/JETIR1905Y54.pdf