计算机视觉
人工智能
跟踪(教育)
计算机科学
视频跟踪
光学(聚焦)
目标检测
对象(语法)
跟踪系统
眼动
图像(数学)
干扰(通信)
稳健性(进化)
图像处理
图像复原
光源
作者
Siyuan Wang,H F,Chen Wang,Han Luo,Y Jiang
摘要
Mainstream object tracking models primarily focus on exploring diverse attention mechanisms, advancing multi-camera perspective-based designs, and developing multi-modal frameworks. In contrast, the most remarkable progress has been witnessed in the fields of image generation and image restoration—achievements that have not yet been cross-domain integrated into object tracking models. To tackle the challenge in engineering practice where light beam echo spots degrade tracking performance, we propose a novel tracking framework that fuses image restoration with object tracking. Specifically, the framework first restores regions occluded by light spots, followed by performing tracking on the restored images. This design significantly enhances the performance of object tracking models on datasets contaminated by light spot interference.
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