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A new approach for vehicle detection performs sensor fusion of a laser scanner and a video sensor. This combination provides enough information to handle the problem of multiple views of a car. The laser scanner estimates the distance as well as the contour information of observed objects. The contour information can be used to identify the discrete sides of rectangular objects in the laser scanner coordinate system. The transformation of the three-dimensional coordinates of the most visible side to the image coordinate system allows for a reconstruction of its original view. This transformation also compensates size differences in the video image, which are caused by different distances to the video sensor. Afterwards, a pattern recognition algorithm can classify the object's sides based on contour and shape information. Since the number of available object hypotheses is enormously reduced by the laser scanner, the system is applicable in real time. In addition, video-based vehicle detection and additional laser scanner features are fused in order to create a consistent vehicle environment description.