DocumentCode
2399532
Title
Transductive object cutout
Author
Cui, Jingyu ; Yang, Qiong ; Wen, Fang ; Wu, Qiying ; Zhang, Changshui ; Van Gool, Luc ; Tang, Xiaoou
Author_Institution
Tsinghua Univ., Beijing
fYear
2008
fDate
23-28 June 2008
Firstpage
1
Lastpage
8
Abstract
In this paper, we address the issue of transducing the object cutout model from an example image to novel image instances. We observe that although object and background are very likely to contain similar colors in natural images, it is much less probable that they share similar color configurations. Motivated by this observation, we propose a local color pattern model to characterize the color configuration in a robust way. Additionally, we propose an edge profile model to modulate the contrast of the image, which enhances edges along object boundaries and attenuates edges inside object or background. The local color pattern model and edge model are integrated in a graph-cut framework. Higher accuracy and improved robustness of the proposed method are demonstrated through experimental comparison with state-of-the-art algorithms.
Keywords
edge detection; graph theory; image colour analysis; image enhancement; object detection; color configuration; edge enhancement; edge profile model; graph-cut framework; image instance; local color pattern model; natural image colour analysis; object boundary; transductive object cutout model; Asia; Histograms; Image segmentation; Learning systems; Machine learning; Machine learning algorithms; Object segmentation; Optimized production technology; Pixel; Robustness;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on
Conference_Location
Anchorage, AK
ISSN
1063-6919
Print_ISBN
978-1-4244-2242-5
Electronic_ISBN
1063-6919
Type
conf
DOI
10.1109/CVPR.2008.4587589
Filename
4587589
Link To Document