Name
Abstract | ||
|---|---|---|
Recognition from partial views is a practical need for autonomous vehicles. Acquiring enough detailed information is not always possible. For avoiding obstacles we need partial recognition from a distance, before we have a full scanning in a dangerously close position. However, there are very few applicable results, especially in case of 3D. In this paper validation tests are presented for a method developed for partial recognition from 3D. For the real-life tests urban scenes of Mobile Laser Scanning data was selected. On the noisy LIDAR data, the excellent applicability of the method is proved. This paper shows the efficiency of the proposed method in real-life street scenery. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/IWCIM.2016.7801185 | 2016 International Workshop on Computational Intelligence for Multimedia Understanding (IWCIM) |
Keywords | Field | DocType |
Point cloud,keypoint detection,object recognition,LIDAR,Mobile Laser Scanning | Object detection,Computer vision,Mobile laser scanning,Lidar,Artificial intelligence,Lidar data,Point cloud,Geography,Cognitive neuroscience of visual object recognition | Conference |
ISBN | Citations | PageRank |
978-1-5090-5525-8 | 0 | 0.34 |
References | Authors | |
7 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zoltan Rozsa | 1 | 0 | 0.34 |
| Tamás Szirányi | 2 | 152 | 26.92 |