• Dr. Navneet S. Ghedia
• Dr. C. H. Vithalani
• Dr. Ashish Kothari

Proficient categorization of the foreground and background is very critical and essential for the Visual Surveillance system. Identify the motion in the video sequences or the real time analysis, foreground classification in the basic operation hence the reliability of the surveillance system is completely depends on the segmentation approach. A large no. of algorithms and experiments are proposed and implemented for the moving object classification, recognition and detection. All approaches are usually available with the tradeoffs like computational cost, quality and accuracy of the foreground detection, environmental conditions and surveillance applications. The purpose of the paper is to present the exhaustive and comprehensive literature and study for the background estimation, background modeling and statistical foreground classification approaches. The efficacy of all the algorithm varies due to their feature properties and way of adopting the surveillance applications. In this paper we have provided the exhaustive and popular statistical pixel based parametric and non parametric approaches for the foreground detection. In all-purpose our plan is to provide the critical relative analysis of almost all the available background modeling approaches, so the researchers can effortlessly accept and modified the background model as per their requirements and applications.

Background Estimation, Statistical Background Modeling, Foreground Detection, Visual Monitoring.

"Statistical Background Estimation for Robust Foreground Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.406-410, May 2019, Available :http://www.jetir.org/papers/JETIR1905Y59.pdf

"Statistical Background Estimation for Robust Foreground Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp406-410, May 2019, Available at : http://www.jetir.org/papers/JETIR1905Y59.pdf