Fusion of Multi-View Silhouette Cues Using a Space Occupancy Grid

In this paper, we investigate what can be inferred from several silhouette probability maps, in multi-camera environments. To this aim, we propose a new framework for multi-view silhouette cue fusion. This framework uses a space occupancy grid as a probabilistic 3D representation of scene contents. Such a representation is of great interest for various computer vision applications in perception, or localization for instance. Our main contribution is to introduce the occupancy grid concept, popular in the robotics community, for multi-camera environments. The idea is to consider each camera pixel as a statistical occupancy sensor. All pixel observations are then used jointly to infer where, and how likely, matter is present in the scene. As our results illustrate, this simple model has various advantages. Most sources of uncertainty are explicitly modeled, and no premature decisions about pixel labeling occur, thus preserving pixel knowledge. Consequently, optimal scene object localiza...

• Type: Conference
• Year: 2005
• Where: ICCV
• Authors: Jean-Sébastien Franco, Edmond Boyer
• Keywords: Computer Vision, ICCV 2005, Multi-view Silhouette Cue, Occupancy Grid Concept, Pixel Labeling Occur, Space Occupancy Grid, Statistical Occupancy Sensor