Title: Adaptive background modelling technique for moving object detection in video under dynamic environment
Authors: Dileep Kumar Yadav; Karan Singh
Addresses: School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, India ' School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, India
Abstract: This work proposes a novel method for detection of motion based object having dynamic scenario in the background. The suggested scheme has a strong potential for real-time applications especially for rafting, river, sea-beach, swimming pools, ponds, etc. Apart from these, this work is very beneficial for surveillance of border, tunnel, traffic in the sea, forest, restricted zones, deep zones, etc. This work develops a statistical p based background subtraction method and implemented in three stages. In the first stage, a background model is developed using few initial frames. In the second stage, this work classifies the foreground using the difference frame and the appropriate threshold value. An automatic threshold value is generated at run-time and updated iteratively. It also reduces the problem of using a constant threshold. In the third stage, morphological filters and connected component based region filtering technique is applied to enhance the detection quality. The extensive experimental result shows more accurate results of proposed method. It also demonstrates better performance against considered state-of-the-art methods.
Keywords: cluttered background; adaptive modelling; background subtraction; outliers; moving object segmentation; visual surveillance.
International Journal of Spatio-Temporal Data Science, 2019 Vol.1 No.1, pp.4 - 21
Received: 06 Oct 2016
Accepted: 15 May 2017
Published online: 31 Jan 2019 *