Hierarchical detection of moving targets on moving platforms

In the context of driving assistance, detection of moving targets is challenging when the automobile is witnessing very complex environment. The main challenges come from difficulties to tell foreground from moving background due to camera motion. We present an efficient method for target detection by hierarchically distinguishing the motion of targets from that of the background and using color information to help with the process. Firstly, point features are extracted and tracked to form feature trajectories. Secondly, distance measures are defined on the trajectories and hierarchically used to cluster the generated trajectories into regions. The last step is devoted to better detection of the targets by adding appearance information. Experiments show our method is able to give target detection results in real time even in very complex environments.