Abstract
An algorithm of vehicle type recognition integrating on-board sensor information is proposed. This method, compensates for apparent size differences due to the objective distances of on-board sensors, the distance and intensity detected by a scanning laser radar, and the images input from an on-board CCD camera. A frame recognition which consists of a multiplex structured neural network using the three kinds of adjusted data is performed, then the results are integrated to improve the accuracy of the recognition of each object. Experiments using road images captured while driving and the sensing data show that this method is effective : average recognition rates were above 96.1% for various road environments.
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