基于SIFT和YOLO的弱目标鲁棒性实时追踪算法

Weak Target Robust Real-time Tracking Algorithm Based on SIFT and YOLO

提出基于SIFT和YOLO的弱目标鲁棒性实时追踪算法,它能够在场景变化剧烈、目标存在遮挡等复杂条件下对目标进行持续稳定的追踪。算法的实现以合理的算法架构设计为基础,利用YOLO选择候选目标,利用SIFT从候选目标中选择被追踪目标。本文提出的追踪算法不仅满足实时性要求,而且在正常测试集、目标存在遮挡测试集、摄像头旋转测试集上均取得了优于KCF和Cam Shift的实验结果。结果表明,本文提出的追踪算法在解决目标遮挡、场景变化剧烈等问题上有突出表现。

This paper proposes a robust real-time tracking algorithm for weak targets based on SIFT and YOLO. It can continuously and steadily track the target under complex conditions such as dramatic scene changes and object occlusion. The implenlenration of the algorithm is based on a reasonable algorithm architecture design, uses YOLO to select candidate targets, and uses SIFT to select the tracked targets from the candidate targets. The tracking algorithm proposed in this paper not only meets the real- time performance, but also obtains better experimental results than KCF and CamShift in the normal test set, the target existence occlusion test set, and the camera rotation test set. The results show that the tracking algorithm proposed in this paper has out- standing performance in solving problems such as target occlusion and dramatic scene changes.