loading...
Robust Object Segmentation Using Graph Cut with Object and Background Seed Estimation
Hong Kong August 20-August 24
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2006.101218th International Conference on Patt ...
 This Article 
 
PDF
HTML
 
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Jung-Ho Ahn, Yonsei University, Seoul, Korea
KilCheon Kim, Yonsei University, Seoul, Korea
Hyeran Byun, Yonsei University, Seoul, Korea
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.
Citation:
Jung-Ho Ahn, KilCheon Kim, Hyeran Byun, "Robust Object Segmentation Using Graph Cut with Object and Background Seed Estimation," icpr, vol. 2, pp.361-364, 18th International Conference on Pattern Recognition (ICPR'06) Volume 2, 2006
Usage of this product signifies your acceptance of the Terms of Use.