Proceedings of the Korean Society of Broadcast Engineers Conference (한국방송∙미디어공학회:학술대회논문집)
- 2009.01a
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- Pages.148-153
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- 2009
PROPAGATION OF MULTI-LEVEL CUES WITH ADAPTIVE CONFIDENCE FOR BILAYER SEGMENTATION OF CONSISTENT SCENE IMAGES
- Lee, Soo-Chahn (School of EECS, Seoul National University) ;
- Yun, Il-Dong (School of EIE, Hankuk University of Foreign Studies) ;
- Lee, Sang-Uk (School of EECS, Seoul National University)
- Published : 2009.01.12
Abstract
Few methods have dealt with segmenting multiple images with analogous content. Concurrent images of a scene and gathered images of a similar foreground are examples of these images, which we term consistent scene images. In this paper, we present a method to segment these images based on manual segmentation of one image, by iteratively propagating information via multi-level cues with adaptive confidence. The cues are classified as low-, mid-, and high- levels based on whether they pertain to pixels, patches, and shapes. Propagated cues are used to compute potentials in an MRF framework, and segmentation is done by energy minimization. Through this process, the proposed method attempts to maximize the amount of extracted information and maximize the consistency of segmentation. We demonstrate the effectiveness of the proposed method on several sets of consistent scene images and provide a comparison with results based only on mid-level cues [1].