Background model based on intensity change similarity among pixels

Satoshi Yoshinaga, Atsushi Shimada, Hajime Nagahara, Rin-Ichiro Taniguchi

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

17 Citations (Scopus)

Abstract

Object detection is an important task for computer vision applications. Many researchers have proposed a lot of methods to detect the objects through the background modeling. Most of previous approaches model the background independently for each pixel and detect foreground objects based on it. Then, it is difficult for the background model to deal with illumination changes, which cause significant intensity changes as in the case that a foreground object appears. To solve this problem, in this paper, we propose a new background model considering the similarity in the intensity changes among pixels. In particular, we classify all the pixels into several clusters based on the similarity of their intensity changes. Then, focusing on each cluster, we can easily identify whether the significant intensity changes are caused by foreground objects or illumination changes. This is because, if the illumination changes, most of the pixels belonging to the same cluster exhibit the similar intensity changes.

Original languageEnglish
Title of host publicationFCV 2013 - Proceedings of the 19th Korea-Japan Joint Workshop on Frontiers of Computer Vision
Pages276-280
Number of pages5
DOIs
Publication statusPublished - Apr 15 2013
Event19th Korea-Japan Joint Workshop on Frontiers of Computer Vision, FCV 2013 - Incheon, Korea, Republic of
Duration: Jan 30 2013Feb 1 2013

Publication series

NameFCV 2013 - Proceedings of the 19th Korea-Japan Joint Workshop on Frontiers of Computer Vision

Other

Other19th Korea-Japan Joint Workshop on Frontiers of Computer Vision, FCV 2013
CountryKorea, Republic of
CityIncheon
Period1/30/132/1/13

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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