Robust object segmentation using graph cut with object and background seed estimation

Jung Ho Ahn, Kil Cheon Kim, Hyeran Byun

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

9 Citations (Scopus)

Abstract

In this paper we propose a new robust way of extracting accurate human silhouettes indoors with an active stereo camera. We first infer the parts of object and background areas of high confidence by fusing color, stereo matching information and image segmentation methods. Then the inferred areas(seeds) are incorporated in a graph cut. The experimental results were presented with image sequences taken with pan-tilt stereo camera. Our proposed algorithms were evaluated with respect to the ground truth data. We proved that our algorithms can outperform other methods that are based on either color/contrast or stereo/contrast principles alone.

Original languageEnglish
Title of host publicationProceedings - 18th International Conference on Pattern Recognition, ICPR 2006
Pages361-364
Number of pages4
DOIs
Publication statusPublished - 2006
Event18th International Conference on Pattern Recognition, ICPR 2006 - Hong Kong, China
Duration: 2006 Aug 202006 Aug 24

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume2
ISSN (Print)1051-4651

Other

Other18th International Conference on Pattern Recognition, ICPR 2006
CountryChina
CityHong Kong
Period06/8/2006/8/24

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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