A Point-Based Tracking Algorithm for Vehicle Trajectories in Complex Environment
Sheng-Nan Lu, Song Huansheng, Cui Hua, Wang Guofeng · 2014
In this paper, a point-based tracking algorithm is presented, which can be used in traffic jams and complex weather conditions. The main approaches for tracking vehicle trajectories are based on accurately segment for the moving vehicles, while uneven illumination, shadows and vehicle overlapping are difficult to handle. The main contribution of this paper is to propose a point tracking algorithm for vehicle trajectories without a difficult image segmentation procedure. In the proposed algorithm, feature points are extracted using an improved Moravec algorithm. A specially designed template is used to track the feature points through the image sequences. Then trajectories of feature points can be obtained, while unqualified track trajectories are removed using decision rules. The experiment results show that the algorithm is robust enough for vehicle tracking in complex weather conditions.