Name
Abstract | ||
|---|---|---|
We present a monocular obstacle avoidance method based on a novel image feature map built by fusing robust saliency features, to be used in embedded systems on lightweight autonomous vehicles. The fused salient features are a textural-directional Harris based feature map and a relative focus feature map. We present the generation of the fused salient map, along with its application for obstacle avoidance. Evaluations are performed from a saliency point of view, and for the assessment of the method's applicability for obstacle avoidance in simulated environments. The presented results support the usability of the method in embedded systems on lightweight unmanned vehicles. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/ICCVW.2017.92 | 2017 IEEE International Conference on Computer Vision Workshops (ICCVW) |
Keywords | Field | DocType |
lightweight monocular obstacle avoidance,monocular obstacle avoidance method,robust saliency features,embedded systems,lightweight autonomous vehicles,fused salient features,textural-directional Harris based feature map,relative focus feature map,fused salient map,lightweight unmanned vehicles,image feature map,salient feature fusion | Obstacle avoidance,Computer vision,Feature fusion,Pattern recognition,Computer science,Visualization,Salience (neuroscience),Usability,Feature extraction,Artificial intelligence,Monocular,Salient | Conference |
Volume | Issue | ISSN |
2017 | 1 | 2473-9936 |
ISBN | Citations | PageRank |
978-1-5386-1035-0 | 0 | 0.34 |
References | Authors | |
25 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrea Manno-Kovacs | 1 | 13 | 3.02 |
| Levente Kovács | 2 | 98 | 38.25 |