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The aim of this paper is to present a multiple object tracking data fusion technique, which fuses radar, image, and ego vehicle odometry. The data are fused at a high level, which leads to reliable and stable tracking results providing also additional features as width estimation and the detection of stationary objects. A ldquorealrdquo application of these algorithms is illustrated on a specific...
In the scope of the EU funded TRACKSS project on cooperative advanced sensors for road traffic applications, we investigate the potential of pre-existing road traffic sensors for pedestrian crossing detection. Two road traffic video-sensors provide spatial occupancy rates on areas along a crosswalk. We propose to correct pedestrian under-detection with a double fusion process composed of inter-sensor...
This paper proposes a new method for multisensor background extraction and updating aimed at surveillance and target detection applications. The background scene extraction is based on robust multisensor change detection of moving objects in the scene. An iterative mechanism updates the background estimate using this information thereby ignoring transient objects but allowing for slow changes in scene...
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