Name
Abstract | ||
|---|---|---|
We present a novel 2D-3D matching method, which is applicable to the pose detection of a target 3D object for an AR application. Our method matches 2D keypoints against their corresponding 3D points directly with a classification approach, and implements a matching refinement using geometric restriction. Our method achieves robust matching and handles the problem that the performance of the conventional keyframe-based methods relies on the pose of the target object in reference images due to self-occlusion. In our experiment, our method improved the matching performance of the conventional method by 15 percentage points. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2407746.2407757 | SIGGRAPH Asia 2012 Technical Briefs |
Keywords | DocType | Citations |
robust matching,matching performance,conventional method,target object,geometric restriction,ar application,conventional keyframe-based method,percentage point,classification approach,matching refinement,augmented reality | Conference | 1 |
PageRank | References | Authors |
0.36 | 7 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tatsuya Kobayashi | 1 | 7 | 3.38 |
| Haruhisa Kato | 2 | 40 | 11.47 |
| Akio Yoneyama | 3 | 117 | 17.49 |