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Volume 33 Issue 4
May  2011
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Zhu Yun-Feng, Zhang Yu-Jin. Transductive Co-segmentation of Multi-view Images[J]. Journal of Electronics & Information Technology, 2011, 33(4): 763-768. doi: 10.3724/SP.J.1146.2010.00839
Citation: Zhu Yun-Feng, Zhang Yu-Jin. Transductive Co-segmentation of Multi-view Images[J]. Journal of Electronics & Information Technology, 2011, 33(4): 763-768. doi: 10.3724/SP.J.1146.2010.00839

Transductive Co-segmentation of Multi-view Images

doi: 10.3724/SP.J.1146.2010.00839
  • Received Date: 2010-08-09
  • Rev Recd Date: 2011-01-14
  • Publish Date: 2011-04-19
  • Fast and efficient segmentation of rigid or stable object in multi-view images is still a unsolved problem. In this paper, the problem is formulated and the relationships between it and traditional min-cut based segmentation problems are also deduced with Graph representation. To minimize the energy function, a novel algorithm named Interactive Transductive Co-Segmentation (ITC-Seg) is proposed. In ITC-Seg, the function is divided into two sub problems which are solved with graph cuts and spectral segmentation methods. Moreover, propagation, filter, voting methods are introduced into the iteration between multi-view images segmentation and qusi-sparse 3D points segmentation, they are used to combine the sub problems with a global label consistent constrains. Finally, the experiments in several images show the error rate of ITC-Seg is 3.4%, discussions and future improvements of the method are also given.
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