Video-based vehicle tracking considering occlusion  

考虑遮挡的视频车辆跟踪（英文）

作　　者：朱周[1,2] 路小波[3,2] 

机构地区：[1]东南大学交通学院,南京210096 [2]东南大学复杂工程系统测量与控制教育部重点实验室,南京210096 [3]东南大学自动化学院,南京210096

出　　处：《Journal of Southeast University(English Edition)》2015年第2期266-271,共6页东南大学学报（英文版）

基　　金：The National Natural Science Foundation of China(No.60972001,61374194)

摘　　要：To track the vehicles under occlusion, a vehicle tracking algorithm based on blocks is proposed. The target vehicle is divided into several blocks of uniform size, in which the edge block can overlap its neighboring blocks. All the blocks＇ motion vectors are estimated, and the noise motion vectors are detected and adjusted to decrease the error of motion vector estimation. Then, by moving the blocks based on the adjusted motion vectors, the vehicle is tracked. Aiming at the occlusion between vehicles, a Markov random field is established to describe the relationship between the blocks in the blocked regions. The neighborhood of blocks is defined using the Euclidean distance. An energy function is defined based on the blocks＇ histograms and optimized by the simulated annealing algorithm to segment the occlusion region. Experimental results demonstrate that the proposed algorithm can track vehicles under occlusion accurately.为了对遮挡情况下的运动车辆进行跟踪,提出一种基于分块的车辆跟踪算法.该算法将目标车辆以可重叠的方式划分为若干大小一致的子块.在分块的基础上估计所有子块的运动矢量,检测噪声运动矢量并进行调整,以减少运动矢量估计的误差,然后对子块进行移位以实现车辆跟踪.为了处理车辆间的遮挡现象建立了马尔可夫随机场描述子块之间的关系,利用欧氏距离定义块的邻域,并基于块的直方图构建能量函数,最后利用模拟退火法对能量函数进行优化,以对遮挡区域进行分割.实验结果表明,该算法能够对遮挡车辆进行准确跟踪.

关 键 词：vehicle tracking occlusion processing motionvector Markov random field 

分 类 号：U491.1[交通运输工程—交通运输规划与管理]