Acta Optica Sinica, Volume. 39, Issue 7, 0715006(2019)
Stereo Matching Algorithm Based on Pixel Category Optimized PatchMatch
Fig. 4. Cross windows. (a) Expansion regions for different groups; (b) local image region
Fig. 6. Multi-category graphs. (a) Plastic; (b) Meanshift; (c) SNIC; (d) texture structure graph
Fig. 8. Comparison of error rates between improved generation mechanism and the original method in one iteration
Fig. 9. Filling methods. (a) Texture region; (b) texture-less region. Red regions represent stable points, black regions represent unstable points, and white regions represent culling points
Fig. 13. Disparities of some global PatchMatch algorithms (points with error matching rate greater than 1 pixel are shown in red). (a) Image; (b) PMBP; (c) SPM-BP; (d) GCLSL; (e) PMSC; (f) LocalExp; (g) proposed
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Yakun Gao, Tao Liu, Haibin Li, Wenming Zhang. Stereo Matching Algorithm Based on Pixel Category Optimized PatchMatch[J]. Acta Optica Sinica, 2019, 39(7): 0715006
Category: Machine Vision
Received: Jan. 3, 2019
Accepted: Apr. 1, 2019
Published Online: Jul. 16, 2019
The Author Email: Li Haibin (hbli@ysu.edu.cn)