光电工程, 2009, 36 (2): 11, 网络出版: 2009-10-09
基于Mean Shift 算法的伪装目标跟踪
Camouflaged Target Tracking Based on Mean Shift
目标跟踪 伪装目标 联合直方图 自适应权重 target tracking Mean Shift Mean Shift camouflaged target joint histogram adaptive weight
摘要
针对传统Mean Shift 跟踪算法对伪装目标进行跟踪时容易陷入局部最大值导致跟偏甚至跟丢的问题,本文首先采用联合直方图来增强对目标特征的描述,然后在跟踪过程中以目标背景区分度为原则,动态更改目标描述模型和通过调整联合直方图各部分的权重来自适应背景的变化,以保证跟踪此类目标的鲁棒性。实验证明,针对与背景相似的伪装目标,改进的Mean Shift 算法仍能对其进行有效准确的跟踪。
Abstract
An improved tracking algorithm is presented in order to solve the problem that traditional tracking algorithm based on Mean Shift often falls into local extrema and causes inaccuracy or even failure when tracking a camouflaged target. Firstly, joint histogram is used to enhance the description of camouflaged target’s character. Secondly, target description model is modified according to the discrimination between the target and local background during the tracking period. Finally, the weights of each part of the joint histogram are adjusted adaptively to ensure more accuracy and robustness to background motions. The updated algorithm is tested with image sequences where the colors for both the target and the background are similar and results show that it can achieve effective and exact tracking.
颜佳, 吴敏渊, 陈淑珍, 张青林. 基于Mean Shift 算法的伪装目标跟踪[J]. 光电工程, 2009, 36(2): 11. YAN Jia, WU Min-yuan, CHEN Shu-zhen, ZHANG Qing-lin. Camouflaged Target Tracking Based on Mean Shift[J]. Opto-Electronic Engineering, 2009, 36(2): 11.