Name
Abstract | ||
|---|---|---|
In this paper, a local method is proposed to estimate the visibility and disparity of pixels from a stereo pair using the DAISY feature. The problem is formulated as a joint optimization over disparity and visibility of individual pixels. The constraints on the range of disparities and the binary visibility variables are enforced by incorporating penalty terms into the cost function. Finally, the unconstrained optimization problem is solved using a Newton scheme with appropriate approximations to the Hessian matrices and gradients. The computation time of the proposed optimization method is around one minute to run for 768 x 512 stereo pairs using the DAISY feature descriptor in a C++ implementation. |
Year | Venue | Keywords |
|---|---|---|
2017 | 2017 24TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) | stereo matching, local optimization, the DAISY feature vector |
Field | DocType | ISSN |
Local method,Computer vision,Visibility,Computer science,Matrix (mathematics),Hessian matrix,Artificial intelligence,Pixel,Optimization problem,Binary number,Computation | Conference | 1522-4880 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaoming Peng | 1 | 95 | 20.72 |
| Abdesselam Bouzerdoum | 2 | 883 | 89.51 |
| Son Lam Phung | 3 | 625 | 48.64 |