Name
Abstract | ||
|---|---|---|
This work presents a method for segmenting image patches which correspond to planar regions in the scene. The method consists of an efficient and robust solution for detecting multiple planar regions in a global optimal sense. Moreover, in contrast with existing techniques which also work on intensity images, neither assumptions about the scene are made nor heuristic hypotheses are formulated. More specifically, the proposed method is based on a systematic, progressive voting procedure from the solution of a linear system, which exploits the two-view geometry. Hence, besides avoiding intermediary depth maps, the progressive mechanism together with such a convergence mapping drastically reduce the computational and storage complexities of the approach. Results from both synthetic and real-world scenes in different scenarios and under various kinds of strong noise confirm its effectiveness and robustness against large camera calibration errors and to the presence of outliers. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/IROS.2006.282189 | 2006 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, VOLS 1-12 |
Keywords | Field | DocType |
depth map,linear system,global optimization,image segmentation,real time,geometry,camera calibration | Computer vision,Object detection,Heuristic,Scale-space segmentation,Linear system,Computer science,Segmentation-based object categorization,Robustness (computer science),Image segmentation,Camera resectioning,Artificial intelligence | Conference |
Citations | PageRank | References |
15 | 1.14 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Geraldo F. Silveira | 1 | 202 | 12.78 |
| Ezio Malis | 2 | 1322 | 80.65 |
| Patrick Rives | 3 | 254 | 17.77 |