湖南大学学报（自然科学版）2012，Vol.39Issue(7)：31-36,6.
一种基于Mean Shift和C-V模型的车辆跟踪算法
A Vehicle Tracking Algorithm Based on Mean Shift and C-V Model
摘要
Abstract
The traditional mean shift algorithm uses the tracking window of fixed size, so it is not efficient to track target vehicle, which continuously changes in size. To solve this problem, this paper presented a new vehicle tracking algorithm according to the characteristic of tracked vehicle. The new algorithm is based on the combination of mean shift and C-V model. Firstly, the initial tracking window was obtained with traditional mean shift tracking algorithm, then the tracking window was shifted and reshaped according to the shape information of target vehicle obtained by C-V model. In the tracking process, the shape and color information were both considered. Meanwhile, an improved C-V model was proposed, which used a new level set initialization function. Experiment results have shown that the tracking algorithm improves vehicle tracking accuracy greatly and guarantees real-time tracking.关键词
车辆跟踪/Mean Shift算法/C-V模型/单目视觉Key words
vehicle tracking/ mean shift algorithm/ C-V model/ monocular vision分类
信息技术与安全科学引用本文复制引用
解文华,肖进胜,易本顺,张亚琪,李明..一种基于Mean Shift和C-V模型的车辆跟踪算法[J].湖南大学学报（自然科学版）,2012,39(7):31-36,6.基金项目
国家自然科学基金资助项目(41001306) （41001306）
湖北省自然科学基金资助项目(2009cdb328) （2009cdb328）
