Séminaire (Organisé par l’Equipe de recherche DI)

Philippe XU

Doctorant Heudiasyc

Information Fusion for Scene Understanding

Mardi 7 janvier 2014 à 14h en salle A108

Résumé :

The large number of tasks one may expect from a driver assistance system leads to consider many object classes in the neighborhood of the so-called intelligent vehicle.

In order to get a correct understanding of the driving scene, one has to fuse all sources of information that can be made available. We propose an original fusion framework working on segments of over-segmented images and based on the theory of belief functions. The problem is posed as an image labeling one.

The main novelty of the framework is its capability to incorporate new classes of objects and to include new sensors or detection methods while remaining robust to sensor failures. 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 dcene data.


FR SHIC 3272

Collegium UTC/CNRS