Vehicles detection using sensor fusion

Sensor fusion method is more robust than the method using a single sensor, so sensor fusion is effective for vehicle recognition in a complex scene. However, if each sensing data is processed individually for most of the stages, recognition performance is not always good. In this paper, we propose the extensible and generalized fusion method. First, fusion vector which is combined with image sensor data and laser radar data at a primitive level is prepared. We regard fusion vector as sensing data by one robust sensor. Next, fusion vector is compared with a discriminated dictionary. We report the efficiency of our method at a complex scene in which recognition error tends to occur by using a single sensor.