Robust region extraction of moving objects in dynamic background

Shun Mori, Yuya Kasahara, Toru Abe, Takuo Suganuma

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

1 Citation (Scopus)

Abstract

We propose a novel background subtraction method for robust region extraction of moving objects in the dynamic background. In our method, a set of recently observed frame (reference) images is used as a background model. To withstand the constant fluctuations of background appearance, a current frame (input) image is compared with every reference image, and pixels in the input image deviated from those in the reference images are extracted as moving object regions. Such a simply-structured background model enables our method to adaptively vary the size of a spatial block for comparing the input image with the reference images. Setting an appropriate size block for each subject pixel in the input image, our method increases the stability of image comparison, and then improves the robustness of region extraction. Experimental results indicate that our method outperforms the existing methods in the region extraction accuracy of moving objects in the dynamic background.

Original languageEnglish
Title of host publication2016 23rd International Conference on Pattern Recognition, ICPR 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1971-1976
Number of pages6
ISBN (Electronic)9781509048472
DOIs
Publication statusPublished - 2016 Jan 1
Event23rd International Conference on Pattern Recognition, ICPR 2016 - Cancun, Mexico
Duration: 2016 Dec 42016 Dec 8

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume0
ISSN (Print)1051-4651

Other

Other23rd International Conference on Pattern Recognition, ICPR 2016
CountryMexico
CityCancun
Period16/12/416/12/8

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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