Pedestrian and vehicle detection and tracking with object-driven vanishing line estimation

To robustly detect people and vehicle on the road in a video sequence is a challenging problem. Most researches focus on detecting or tracking of specific targets only. On the contrary, instead of detecting vehicle or pedestrian individually, an integration framework combining the geometric information is proposed. The camera’s pitch angle is estimated with a novel vanishing line estimator. Not only detecting the vanishing point using line intersection approach, but also the object information from tracker are considered. Specifically, the detected vehicle or pedestrian will cast votes for the hypothesized horizon line. The vanishing line can be estimated even when the scenes are cluttered or crowded, and thus the geometric information can be estimated under challenging circumstance. In turn, such information of scene can help the system refine our detection results through Bayes’ network. Finally, to verify the performance of the system, comprehensive experiments have been conducted with the KITTI dataset. It is quite promising that the state-of-the-art detector, in our case, Regionlet detector, can be improved.