Multiple Objects Segmentation from Multi-View Sequence

Q. Zhang and K.N. Ngan (PRC)


Object extraction, disparity projection, graph cut, multiview segmentation.


This paper proposes an automatic algorithm to segment multiple objects from the initial frame of the multi-view sequence. Firstly, saliency based visual attention model is adopted in the key view of image to detect the location of objects-of-interest (OOIs), followed by the OOIs extraction based on the saliency analysis. Then, the initial mask of the key view is spatially projected by the disparity value to form the ones of the other views. Finally, multiple objects segmentation is decomposed into several sub-segmentation problems and solved by minimizing our proposed energy function using bi-label graph cut to achieve more accurate objects representation. Comparing with a related algorithm on our captured multi-view sequence, experimental results demonstrate the advantage of the proposed algorithm in terms of computational efficiency and segmentation performance.

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