Name
Abstract | ||
|---|---|---|
This paper describes the Pyramidal Block Matching (PBM) stereo method. It uses a pyramidal approach and a global energy function to obtain the disparity image. First, the input images are rectified to obtain row-aligned epipolar geometry. Then the face is segmented out of each image and a face pyramid is generated. The main difference to our approach is that the first layer of pyramid is the whole face. Matching result of the first layer provides input to the next layer, where it is used to constrain the search area for matching. This process continues on each layer. After that, a global energy function is designed to remove the wrong pixels and get a smoother result. A comparison on face images shows that the generated projection results of PBM are the closest to the ground truth images. A face recognition experiment is also performed, and PBM achieves the best recognition rates. |
Year | Venue | Field |
|---|---|---|
2015 | ICIG | Stereo processing,Computer vision,Facial recognition system,Global optimization,Pattern recognition,Epipolar geometry,Stereopsis,Computer science,Ground truth,Pyramid,Artificial intelligence,Pixel |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
12 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jing Wang | 1 | 71 | 38.24 |
| Qiwen Zha | 2 | 0 | 0.68 |
| Yubo Yang | 3 | 18 | 5.22 |
| Yang Liu | 4 | 491 | 116.11 |
| Bo Yang | 5 | 58 | 17.37 |
| Dengbiao Tu | 6 | 0 | 0.34 |
| Guangda Su | 7 | 133 | 20.68 |