计算机视觉
计算机科学
身份(音乐)
对象(语法)
人工智能
边界(拓扑)
跟踪(教育)
视频跟踪
身份变更
数学
心理学
美学
教育学
哲学
感觉
数学分析
社会心理学
作者
guoan cheng,Shengke Wang,Guanhao Yuan
出处
期刊:
日期:2025-02-13
卷期号:: 111-111
摘要
In recent years, UAVs have been widely used in the field of object detection and object counting due to their advantages of high flexibility and strong mobility. When exceeding a certain flight altitude, the drone obtains a wider field of view, captures more objects and improves time efficiency with limited endurance. However, higher flight altitudes mean that drones can collect smaller objects, making it more difficult to detect objects and count them with tracking. When using multi-object tracking for small object counting tasks, this paper proposes a counting algorithm based on changing ID and boundary-aware in the region of interest for the difficult problem that the objects at the far end of the image are too small to track and the objects at the near end always maintain the identity information (ID) unchanged. By setting a suitable region of interest, this paper realizes the counting task with the advantage of not having to track smaller objects at the far end of the image. The tracking-based counting method based on changing ID and boundary-aware proposed in this paper can perform flexible counting when the ID of tracking object changes, which effectively alleviates the adverse impact of ID change on counting accuracy in the counting area of interest.
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