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- W2158624612 abstract "We propose a method for extracting a desired object in multi-view images without camera calibration. We match the corner points obtained automatically by the Scale-invariant feature transform (SIFT) in multiview images, and then connect multi-view images into a weighted undirected graph. Thus, multi-view object segmentation converts to a graph partitioning problem solved by Biased Normalized Cuts. Compared to the existing methods, the main advantages of our method are that: (1) it needn't camera pose and intrinsic parameters; (2) arbitrary view number images (include single image) can be processed. The promising experimental results for images reveal the effectiveness of our approach." @default.
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- W2158624612 date "2012-11-01" @default.
- W2158624612 modified "2023-09-23" @default.
- W2158624612 title "Object segmentation in multiple views without camera calibration" @default.
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