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Liu, R.M. and Yang, M. (2011) Tracking multiple feature in infrared image with mean-shift. Proceedings of the 7th International Conference on Advanced Intelligent Computing, Zhengzhou, 11-14 August 2011.

被以下文章引用:

  • 标题: 实时目标跟踪研究Study on Real-Time Target Tracking

    作者: 胡绍华, 陈勇, 何信华, 沈志军

    关键字: 目标检测, 目标跟踪, 背景减除, 目标匹配Object Detection, Object Tracking, Background Subtraction, Object Matching

    期刊名称: 《Computer Science and Application》, Vol.4 No.8, 2014-08-29

    摘要: 针对图像序列中运动目标检测、跟踪的难点问题,提出了一种实时运动目标检测与跟踪算法。该算法基于自适应背景建模,获取运动目标背景模型和前景图像,从而实现运动目标检测;通过建立运动目标的位置、大小、形状以及颜色分布模型,构造运动目标全局匹配函数,结合目标活力特征,实现多运动目标连续匹配和跟踪。实验结果表明,相对于传统的运动目标跟踪方法,本文方法明显减少了运算时间,增强了环境适应性,实现了复杂场景下运动目标的准确检测和稳定跟踪,对非刚性目标的形变、旋转具有较强的鲁棒性。In this paper, we propose a real-time mobile target detection and tracking algorithm for challenges of mobile target detection and tracking in sequential images. This algorithm based on the adaptive background modeling obtains background model and front-view images of mobile targets, which is the way to achieve target detection. Continuous matching and tracking of multiple mobile targets are realized through constructing position, size, shape and color distribution of the mobile targets, defining a global matching function for those targets, and associating their vitality characteristics. It is demonstrated by experiments that the algorithm presented in this paper, compared to the traditional methods of mobile target tracking, significantly reduces the computation time, improves adaptive feature to environments, achieves accurate detection and robust tracking of mobile targets in complex environments, and shows strong robustness to deformation and rotation of non-rigid targets.

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