计算机科学与探索2026，Vol.20Issue(9)：2623-2635,13.DOI:10.3778/j.issn.1673-9418.2511062
多维空间感知和全局特征调制的鲁棒RGBT目标跟踪
Multi-dimensional Spatial Perception and Global Feature Modulation for Robust RGBT Object Tracking
摘要
Abstract
To address the susceptibility of RGBT object tracking to extreme lighting conditions and cluttered backgrounds in complex scenes,alongside existing methods'inadequate modelling of shared structural information across modalities,this paper proposes an RGBT object tracking approach based on multi-dimensional spatial perception and global feature modulation(multi-dimensional spatial perception network,MSPNet).Firstly,within a dual-stream multi-domain convolu-tional neural network framework,this paper constructs a multi-directional scene awareness(MSA)module.By introduc-ing direction-aware convolutions along horizontal,vertical,and diagonal orientations,this module explicitly models cross-directional spatial dependencies between RGB and infrared features.This overcomes the limitations of traditional convolu-tions in directional modelling,enhancing the interaction and alignment of structural information across modalities.Sec-ondly,a dynamic channel aggregation(DCA)module is designed.Utilizing a branched architecture and decomposable convolutions,it separately models and adaptively fuses channels carrying low-frequency structural information and high-frequency detail information within the dual-modal features.This enhances the discriminative power of multi-scale fea-ture representations.Finally,a global feature modulation(GFM)mechanism is established.This employs adaptive horizon-tal and vertical pooling to obtain direction-aware global contextual representations.Combined with large-kernel striped convolutions,it generates spatial modulation weights that effectively suppress background interference features during the fusion stage,thereby improving foreground object localization accuracy.Experimental results on the GTOT and RGBT234 benchmark datasets demonstrate that MSPNet achieves PR/SR of 90.4%/73.9%and 80.0%/55.8%respectively,exhibiting superior robustness and tracking accuracy compared with existing state-of-the-art trackers.关键词
RGBT跟踪/多域卷积神经网络/多维空间感知/全局特征调制Key words
RGBT tracking/multi-domain convolutional neural network/multi-dimensional spatial perception/global feature modulation分类
信息技术与安全科学引用本文复制引用
洪星,尹明锋,黄舒玥,薄煜明,贝绍轶..多维空间感知和全局特征调制的鲁棒RGBT目标跟踪[J].计算机科学与探索,2026,20(9):2623-2635,13.基金项目
国家自然科学基金(62103192,52172367) （62103192,52172367）
江苏省高校自然科学研究项目(20KJB520015) （20KJB520015）
常州市应用基础研究项目(CJ20200039) （CJ20200039）
江苏省研究生科研与实践创新计划(SJCX24_1786). This work was supported by the National Natural Science Foundation of China(62103192,52172367),the Natural Science Research Project of Jiangsu Provincial Universities(20KJB520015),the Applied Basic Research Project of Changzhou(CJ20200039),and the Graduate Research and Practice Innovation Program of Jiangsu Province(SJCX24_1786). （SJCX24_1786）
