تقرير
The detection and rectification for identity-switch based on unfalsified control
العنوان: | The detection and rectification for identity-switch based on unfalsified control |
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المؤلفون: | Huang, Junchao, He, Xiaoqi, Zhao, Sheng |
سنة النشر: | 2023 |
المجموعة: | Computer Science |
مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence |
الوصف: | The purpose of multi-object tracking (MOT) is to continuously track and identify objects detected in videos. Currently, most methods for multi-object tracking model the motion information and combine it with appearance information to determine and track objects. In this paper, unfalsified control is employed to address the ID-switch problem in multi-object tracking. We establish sequences of appearance information variations for the trajectories during the tracking process and design a detection and rectification module specifically for ID-switch detection and recovery. We also propose a simple and effective strategy to address the issue of ambiguous matching of appearance information during the data association process. Experimental results on publicly available MOT datasets demonstrate that the tracker exhibits excellent effectiveness and robustness in handling tracking errors caused by occlusions and rapid movements. |
نوع الوثيقة: | Working Paper |
URL الوصول: | http://arxiv.org/abs/2307.14591 |
رقم الأكسشن: | edsarx.2307.14591 |
قاعدة البيانات: | arXiv |
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