Résumé
This paper addresses the problem of scene understanding for driver assistance systems. In order to recognize the large number of objects that may be found on the road, several sensors and classification algorithms have to be used. The proposed approach is based on the representation of all available information in over-segmented image regions. The main novelty of the framework is its capability to incorporate new classes of objects and to include new sensors or detection methods. Several classes as ground, vegetation or sky are considered, as well as three different sensors. The approach was evaluated on real and publicly available urban driving scene data.
| Titre traduit de la contribution | Information fusion for scene understanding |
|---|---|
| langue originale | Français |
| Pages (de - à) | 57-80 |
| Nombre de pages | 24 |
| journal | Traitement du Signal |
| Volume | 31 |
| Numéro de publication | 1-2 |
| Les DOIs | |
| état | Publié - 1 janv. 2014 |
| Modification externe | Oui |
mots-clés
- Intelligent vehicles
- Nformation fusion
- Theory of belief functions
- Traffic scene understanding
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