Computer Engineering and Applications ›› 2018, Vol. 54 ›› Issue (6): 205-209.DOI: 10.3778/j.issn.1002-8331.1609-0384

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Complete extraction of trajectories of different vehicles in nighttime city traffic surveillance

TANG Chunming, XIAO Wenna, DONG Yancheng, LIN Xiangqing   

  1. School of Electronical and Information Engineering, Tianjin Polytechnic University, Tianjin 300387, China
  • Online:2018-03-15 Published:2018-04-03



  1. 天津工业大学 电子与信息工程学院,天津 300387

Abstract: The presented tracking system combines the vehicle’s type and trajectory feedback correction in order to obtain the complete trajectory in nighttime traffic surveillance. After filtering the restored headlight blobs in the distant, middle and close regions separately, the initial trajectories of headlights are obtained by area overlapping and trajectory feedback is then used for correction mismatching. Vehicles are classified according to the actual vehicle’s width which is calculated by homography matrix. Based on the temporal and spatial similarity, headlights are paired. The obtained trajectories of vehicles are finally corrected and optimized. The complete extraction of vehicles’ trajectories between the two adjacent monitoring points are achieved. Compared with the other similar algorithms, the number of frames that vehicles are tracked is increased by 500 frames, headlight matching rate is increased by 11.33% and vehicle tracking rate is increased by 10%.

Key words: complete trajectory extraction, vehicles classification, feedback correction

摘要: 针对夜间城市交通视频中各类车辆轨迹的完整提取,提出结合车辆类型与轨迹反馈修正的跟踪系统。在视频远中近区域筛选复原车灯光斑后,用面积重叠法获得车灯初始轨迹,再应用反馈纠正误匹配;通过单应性矩阵推算实际车宽,并依此给车辆分类后,按照时空相似度完成车灯配对;最后修正、优化车辆跟踪结果,实现相邻两个监控点间车辆轨迹的完整提取。与同类算法相比,车辆跟踪帧数增加了500帧,车灯匹配率提高了11.33%,车辆跟踪率提高了10%。

关键词: 轨迹完整提取, 车辆分类, 反馈修正