With the rapid development in computer vision domain, research on object tracking has directed more attention by scholars. Out of view (OV) is an important challenge often encountered in the tracking process of objects, especially in Internet of Things surveillance. Therefore, this paper proposes a fuzzy-aided solution for OV challenge. This solution uses a fuzzy-aided system to detect whether the target is poorly tracked by using the response matrix of samples. When poor tracking occurs, the target is relocated according to the stored template. The proposed solution is tested on OTB100 dataset, where the experimental results show that the auxiliary solution is effective for the OV challenge. The proposed solution also ensures the tracking speed and overall success rate of visual tracking as well as improves the robustness to a certain extent for IoT-assisted complex environment.

随着计算机视觉领域的飞速发展，目标跟踪的研究引起了学者们的更多关注。视线（OV）是对象跟踪过程中经常遇到的重要挑战，尤其是在物联网监视中。因此，本文提出了一种针对OV挑战的模糊辅助解决方案。该解决方案使用模糊辅助系统，通过使用样本的响应矩阵来检测目标是否跟踪不良。当发生不良跟踪时，将根据存储的模板重新定位目标。该解决方案在OTB100数据集上进行了测试，实验结果表明该辅助解决方案对于OV挑战是有效的。