Name
Abstract | ||
|---|---|---|
•An efficient Kernel-Based Hough Transform for detecting planes in depth images.•Summed Area Tables and an implicit quadtree clusterize coplanar points in 2.5-D.•An efficient voting scheme is performed using a trivariate-Gaussian distribution per cluster.•An efficient gradient climbing strategy retrieves the peaks of votes in the accumulator map.•The asymptotic time complexity of our approach is O(n). |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.patrec.2017.12.027 | Pattern Recognition Letters |
Keywords | Field | DocType |
Hough Transform,Plane detection,Depth image,Real time | Cluster (physics),Computer vision,Classification of discontinuities,Pattern recognition,Hough transform,Coplanarity,Gaussian,Artificial intelligence,Point cloud,Mathematics,Scalability,Quadtree | Journal |
Volume | ISSN | Citations |
103 | 0167-8655 | 4 |
PageRank | References | Authors |
0.46 | 12 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Eduardo Vera | 1 | 4 | 0.46 |
| Djalma Lucio | 2 | 72 | 4.38 |
| Leandro A. F. Fernandes | 3 | 206 | 16.22 |
| Luiz Velho | 4 | 1162 | 120.74 |