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Technical Program
Paper Detail
| Paper: | WA-P1.5 |
| Session: | Image and Video Segmentation |
| Time: | Wednesday, October 11, 09:40 - 12:20 |
| Presentation: |
Poster
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| Title: |
MAP-BASED OBJECT EXTRACTION FROM UNCALIBRATED IMAGE PAIR |
| Authors: |
Hyung Il Koo; Seoul National University | | | | | Sang Hwa Lee; Seoul National University | | | | | Nam Ik Cho; Seoul National University | | | | | Seong Keun Kim; SK Telecom | | | | | Dong Hahk Lee; SK Telecom | | | | | Sunghoon Lee; SK Telecom | | |
| Abstract: |
In this paper, we propose a new MAP algorithm for foreground objects extraction from the uncalibrated image pair. The segmentation is modelled as a Markov random field and performed by the MAP framework. The proposed algorithm estimates several spatial transformations between two images by corresponding SIFT points and sequential RANSAC algorithm. And the area-ratio criterion is applied to the each transformation so that we select the transformation of foreground object. Using these transformations, we compute the likelihood of color-segmented subregions. We model the prior information which is based on minimum boundary length and smoothness. Finally, the object extraction is performed by the Bayesian belief propagation. Experimental results on various data sets show good performance to extract the foreground objects from the image pair. |
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