Foreground object detection using two successive images

Jung Ming Wang, Cherng Shen, Chiou Shann Fuh, Sei Wang Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Detecting foreground object often need to face the problems of illumination change and image noise. In this paper, we propose an object detection method using two successive image frames. Illumination change would be very small in such short time, and then we can handle the first problem more easily. Image noise will confuse the detection of an object boundary. To handle this problem, we apply level set method to enclose the foreground object regions. The experiments show that our method can be applied to extract foreground objects in various environments and different cameras.

Original languageEnglish
Title of host publicationProceedings - IEEE 5th International Conference on Advanced Video and Signal Based Surveillance, AVSS 2008
Pages301-306
Number of pages6
DOIs
Publication statusPublished - 2008 Dec 1
EventIEEE 5th International Conference on Advanced Video and Signal Based Surveillance, AVSS 2008 - Santa Fe, NM, United States
Duration: 2008 Sep 12008 Sep 3

Publication series

NameProceedings - IEEE 5th International Conference on Advanced Video and Signal Based Surveillance, AVSS 2008

Other

OtherIEEE 5th International Conference on Advanced Video and Signal Based Surveillance, AVSS 2008
CountryUnited States
CitySanta Fe, NM
Period08/9/108/9/3

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Communication

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  • Cite this

    Wang, J. M., Shen, C., Fuh, C. S., & Chen, S. W. (2008). Foreground object detection using two successive images. In Proceedings - IEEE 5th International Conference on Advanced Video and Signal Based Surveillance, AVSS 2008 (pp. 301-306). [4730429] (Proceedings - IEEE 5th International Conference on Advanced Video and Signal Based Surveillance, AVSS 2008). https://doi.org/10.1109/AVSS.2008.25