An Improved Multiple Interval Pixel Sampling based Background Subtraction Algorithm

개선된 다중 구간 샘플링 배경제거 알고리즘

  • Mahmood, Muhammad Tariq (Korea University of Technology and Education, School of Computer Science and Engineering) ;
  • Choi, Young Kyu (Korea University of Technology and Education, School of Computer Science and Engineering)
  • Received : 2019.07.10
  • Accepted : 2019.09.23
  • Published : 2019.09.30

Abstract

Foreground/background segmentation in video sequences is often one of the first tasks in machine vision applications, making it a critical part of the system. In this paper, we present an improved sample-based technique that provides robust background image as well as segmentation mask. The conventional multiple interval sampling (MIS) algorithm have suffer from the unbalance of computation time per frame and the rapid change of confidence factor of background pixel. To balance the computation amount, a random-based pixel update scheme is proposed and a spatial and temporal smoothing technique is adopted to increase reliability of the confidence factor. The proposed method allows the sampling queue to have more dispersed data in time and space, and provides more continuous and reliable confidence factor. Experimental results revealed that our method works well to estimate stable background image and the foreground mask.

Acknowledgement

Supported by : 한국기술교육대학교

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