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This paper presents Fade, a vehicle detection and tracking system featuring monocular color vision and radar data fusion. Its main originality resides in its low-level fusion system. At each step and for each target, the fusion system fuses the results of four different image processing algorithms and radar information by automatically combining 12 different features and generating many possible target position proposals. It generates a belief network organized in three layers: sources, position proposals, and correlation between proposals. An inference algorithm is then used to find out the actual position of the target, by deducing which observations are wrong. The overall system runs in real time and has been evaluated on a variety of scenarios recorded in a real car using /sup RT/Maps. Fade yields very good detection results in most cases.
Steux et al. (Wed,) studied this question.