Probabilistic background subtraction in a video-based recognition system

Heesung Lee, Sungjun Hong, Euntai Kim

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


In video-based recognition systems, stationary cameras are used to monitor an area of interest. These systems focus on a segmentation of the foreground in the video stream and the recognition of the events occurring in that area. The usual approach to discriminating the foreground from the video sequence is background subtraction. This paper presents a novel background subtraction method based on a probabilistic approach. We represent the posterior probability of the foreground based on the current image and all past images and derive an updated method. Furthermore, we present an efficient fusion method for the color and edge information in order to overcome the difficulties of existing background subtraction methods that use only color information. The suggested method is applied to synthetic data and real video streams, and its robust performance is demonstrated through experimentation.

Original languageEnglish
Pages (from-to)782-804
Number of pages23
JournalKSII Transactions on Internet and Information Systems
Issue number4
Publication statusPublished - 2011 Apr 29

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Networks and Communications


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