鲁棒的前视红外目标多核跟踪算法

针对前视红外目标跟踪中常见的目标位置偏差和部分遮挡问题，在均值漂移算法的框架下，提出了一种基于投影直方图匹配和拓扑约束的多核跟踪算法。首先，对前后帧图像进行基于空间-灰度二维投影直方图匹配的目标位置预测；然后，充分利用目标的前景和背景信息构建多个独立的核跟踪器；最后，采用拓扑约束选取跟踪性能好的核跟踪器，组合得到最终的跟踪结果。实验结果表明:此算法能对目标进行准确跟踪，对目标位置偏差和部分遮挡具有较好的鲁棒性，在有遮挡的情况下，平均跟踪误差远小于传统的跟踪算法。因此，该算法在前视红外成像制导中具有较好的实用性和可行性。

Robust multi-kernel tracking algorithm for FLIR target

A multi-kernel tracking algorithm based on projection histogram matching and topology constraint was proposed in the mean shift framework, in order to overcome problems caused by partial occlusions and location deviation in the forward looking infrared(FLIR) target tracking. Firstly, target location was predicted by matching the spatio-intensity 2D projection histograms of consecutive frames. Secondly, multiple independent kernel-based trackers were built utilizing the target foreground and background information, which could improve the discrimination of the target model. Finally, topology constraint was used to optimize multiple tracking results, and those trackers with better performance were chosen to generate the final tracking result. Experimental results demonstrate that the proposed algorithm can track target accurately and robustly, and especially in the cases of partial occlusions or location deviation, the average tracking error of the proposed algorithm is much less than that of the traditional algorithm. Therefore, the algorithm has high practicality and feasibility in the FLIR imaging guidance.