激光与光电子学进展, 2019, 56 (3): 030401, 网络出版: 2019-07-31
基于相关滤波器的目标抗遮挡算法 下载: 1106次
Target Anti-Occlusion Algorithm Based on Correlation Filter
探测器 相关滤波 抗遮挡 前后向差分检测 detectors correlation filtering anti occlusion forward and backward difference detection
摘要
相关滤波目标跟踪算法是基于目标模板与待测图像之间的相关性大小来实现目标的定位与跟踪,核相关滤波器(KCF)的提出更将其推向了新的高度。然而,通过对KCF算法的深入研究发现,相关滤波器在抗遮挡性能方面有着严重的不足,尤其是在目标短暂消失的情况下十分容易出现跟踪丢失的情况。为了解决这个问题,提出了一种将KCF与前后向误差检测算法相结合的方法,通过前后向误差算法检测遮挡现象,并在遮挡发生后及时保留原目标模板,最后进行小范围的预测并结合原模板重新定位目标位置。实验表明,此方法能有效解决目标短暂完全消失的遮挡状况,并在目标重新出现后进行有效的追踪。
Abstract
Correlation filtering target tracking algorithm is based on the correlation between the target template and the image to be tested to realize the location and tracking of the target. Especially, when the kernelized correlation filters (KCF) is proposed which is faster and more accurate, the correlation filtering target tracking algorithm is pushed to a new height. However, with in-depth study of the KCF algorithm, it is found that the correlation filter has some serious shortcomings in the anti-occlusion performance. Especially in the case of a short-term disappearance of the target, it is extremely easy to lost the target. In order to solve this problem, a method combining KCF with the forward and backward error detecting algorithm is proposed. It detects the occlusion phenomenon by the forward-backward error algorithm, and retains the original target template in time after the occlusion occurs. Finally, it re-locates the position of the target by combing the prediction in a small range with the original template. Experimental results show that this method can effectively solve the occlusion condition when the target disappears completely and perform effective tracking after the target reappears.
王凯宇, 陈志国, 傅毅. 基于相关滤波器的目标抗遮挡算法[J]. 激光与光电子学进展, 2019, 56(3): 030401. Kaiyu Wang, Zhiguo Chen, Yi Fu. Target Anti-Occlusion Algorithm Based on Correlation Filter[J]. Laser & Optoelectronics Progress, 2019, 56(3): 030401.