Computing Visual Correspondence with Occlusions via Graph Cuts

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Left image Right image Horizontal motion (our method) Horizontal motion (method of [8]) Figure 7: Stereo results on the meter image. Occluded pixels are shown in red. 22
Left image Right image Horizontal motion (our method) Horizontal motion (method of [8]) Figure 8: Stereo results on the SRI tree sequence. Occluded pixels are shown in red. 23
Page 1 and 2: Computing Visual Correspondence wit
Page 3 and 4: The new algorithms proposed in this
Page 5 and 6: in the right image. Furthermore, th
Page 7 and 8: • a smoothness term Esmooth, whic
Page 9 and 10: not permit occlusions to be natural
Page 11 and 12: The most closely related work consi
Page 13 and 14: Figure 3: The graph corresponding t
Page 15 and 16: • the last edge that we add is (v
Page 17 and 18: 2. Occlusion term. ˜Eocc(x) = Cp
Page 19 and 20: The corresponding graph is shown in
Page 21: First image Second image Horizontal
Page 25 and 26: distance. Occlusions were computed
Page 27 and 28: 7 Conclusions We have presented an
Page 29 and 30: negative function D : S×V↦→
Page 31 and 32: [7] Yuri Boykov, Olga Veksler, and
Page 33: [23] Rick Szeliski and Ramin Zabih.

Computing Visual Correspondence with Occlusions via Graph Cuts

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