基于动态线索门控与时序增强的多目标跟踪方法和系统

By employing dynamic cue gating and temporal enhancement, the problems of correlation robustness and identity consistency in multi-target tracking under complex scenarios are solved, achieving higher-precision target tracking.

CN122415683APending Publication Date: 2026-07-17SUZHOU UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
SUZHOU UNIV
Filing Date
2026-06-22
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Existing multi-target tracking technologies suffer from insufficient robustness and identity consistency in complex scenarios such as frequent occlusion, nonlinear motion, and appearance drift, leading to a decrease in target tracking accuracy.

Method used

A method based on dynamic cue gating and temporal enhancement is adopted. The temporal feature enhancement network encodes appearance and motion cues, and the cue gating attention fusion module performs dynamic weighted fusion under spatial neighborhood constraints. The trajectory-detection similarity matrix is ​​constructed for matching, the target trajectory state is updated and the identity ID is maintained.

Benefits of technology

It improves the robustness of association and identity consistency in complex scenarios, and enhances the accuracy of target tracking.

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Abstract

本发明涉及计算机视觉技术领域,公开一种基于动态线索门控与时序增强的多目标跟踪方法和系统,包括:获取目标视频,通过目标检测与特征提取形成检测集合,构建历史轨迹集合,集合中的每条轨迹包括外观线索和运动线索;将外观线索和运动线索输入TFEN得到检测端和轨迹端的多线索嵌入,将检测端和轨迹端的多线索嵌入输入CGAF,在空间邻域约束下对不同线索嵌入进行动态门控融合得到融合后的检测嵌入和轨迹嵌入;构造轨迹‑检测相似度矩阵,得到轨迹与检测的匹配结果;根据匹配结果更新目标轨迹状态并维护目标身份ID,输出多目标跟踪结果。本发明可以自适应调节外观线索和运动线索的贡献,抑制噪声影响,提升复杂场景下目标跟踪的准确性。
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