Rear-Vehicle Detection Combining Both Knowledge-Based and Appearance-Based Methods
Huai Yuan · Journal of Northeastern University · 2007
There is unavoidably a limit to either knowledge-based or appearance-based methods when using any of them singly to detect the existence of vehicles.An algorithm combining both of them is therefore proposed to detect rear-vehicles in static images.First,the ROIs(regions of interest) obtained from segmentation algorithm are filtered which are regarded as belonging to background by using knowledge-based methods such as the shadow underneath a vehicle and color information.Then,the vehicles are detected with appearance-based methods on the remains.The detection results of vehicles traveling on highways,urban common roads and urban narrow roads under various illumination conditions on daytime indicated that the proposed algorithm has better reliability and higher adaptability than either of the algorithms singly based on knowledge or appearance.