计算机与现代化Issue(8)：59-66,8.DOI:10.3969/j.issn.1006-2475.2024.08.011
基于改进YOLOX和新型数据关联方式的无人机多目标跟踪方法
Multi-object Tracking of UAV Based on Improved YOLOX and New Data Association Method
付书岗1
作者信息
- 1. 中国科学院空天信息创新研究院,北京 100094||中国科学院空间信息处理与应用系统技术重点实验室,北京 100190||中国科学院大学电子电气与通信工程学院,北京 101408
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摘要
Abstract
Multi-object tracking in UAV videos is a crucial computer vision task with extensive applications across various do-mains.To address the challenges of occlusions,small objects,and complex,varying backgrounds in UAV video scenes,an im-proved UAV multi-object tracking model is proposed.This paper improves the YOLOX network by integrating the Swin Trans-former to enhance global information extraction capabilities and adding an additional detection head to boost the detection perfor-mance of small objects.Furthermore,this paper introduces the CBAM attention module to focus on informative features.In the data association stage,this paper adopts a new data association approach that retains all detection boxes,categorizing them into high-scoring and low-scoring detection boxes based on their confidence scores.The first association is performed between high-scoring detection boxes and tracking trajectories,while the second association is performed between unmatched trajectories and low-scoring detection boxes.Experimental results on the public datasets VisDrone2021 and UAVDT demonstrate that the pro-posed method exhibits relatively high superiority and robustness in UAV multi-object tracking scenarios.关键词
多目标跟踪/无人机视频/注意力机制/数据关联Key words
multi-object tracking/unmanned aerial vehicles(UAV)videos/attention mechanism/data association分类
信息技术与安全科学引用本文复制引用
付书岗..基于改进YOLOX和新型数据关联方式的无人机多目标跟踪方法[J].计算机与现代化,2024,(8):59-66,8.
