低视点下遮挡自适应感知的多目标跟踪算法  

An adaptive occlusion-aware multiple targets tracking algorithm for low viewpoint

作　　者：乐应英 徐丹[1] 贺康建 张浩 Yue Yingying;Xu Dan;He Kangjian;Zhang Hao(School of Information Scienceand Engineering,Yunnan University,Kunming650091,China;School of Mathematics and Information Technology,Yuxi Normal University,Yuxi 653100,China)

机构地区：[1]云南大学信息学院,昆明650091 [2]玉溪师范学院数学与信息技术学院,玉溪653100

出　　处：《中国图象图形学报》2023年第2期441-457,共17页Journal of Image and Graphics

基　　金：国家自然科学基金项目(61761046,61540062,62162068);云南省重大科技专项(202202AD080003)。

摘　　要：目的针对低视点多目标跟踪场景的遮挡问题,提出一种能够遮挡自适应感知的多目标跟踪算法。方法首先根据每帧图像的全局遮挡状态,提出了“自适应抗遮挡特征”,增强目标特征对遮挡的感知和调整能力。同时,采用“级联筛查机制”,减少由遮挡带来的目标特征剧烈变化而认定为“虚新入目标”的错误跟踪现象。最后,考虑到历史模板库中存在遮挡的模板对跟踪性能的影响,根据每一帧中目标的局部遮挡状态,提出自适应干扰模板更新机制,进一步提高对遮挡的应变和适应能力。结果实验结果表明,本文算法在MOTA(multiple object tracking accuracy)、M OTP(multiple object tracking precision)、FN(false negatives)、Rcll(recall)、ML(mostly lost tracklets)等指标上明显优于STAM(spatial-temporal attention mechanism)、ATAF(aggregate tracklet appearance features)、STRN(spatial-temporal relation network)、BLSTMMTPO(bilinear long short-term memory with multi-track pooling)、IADMR(instance-aware tracker and dynamic model refreshment)等典型算法。消融实验表明,自适应抗遮挡特征在MOTA指标上,相比混合特征、外观特征和运动特征分别提升了1.9%、1.8%和13.6%。去干扰模板更新策略在MOTA指标上,相比带权更新策略和常规更新策略分别提升了10.7%和17.7%。结论本文算法在低视点跟踪场景下,能够减弱部分遮挡、短时全遮挡和长时全遮挡对跟踪性能的影响,跟踪鲁棒性得到了提升。Objective Multi-target tracking technique is essential for the computer vision-relevant applications like video surveillance,smart cities,and intelligent public transportation.The task of multi-target tracking is required to better location for multiple targets of each frame through the context information of the video sequence.To generate the motion trajectory of each target,its identity information(ID)is required to keep in consistency.So,we focus on low viewpoint-based multi-target tracking with no high viewpoint involved.For low viewpoint tracking scenes,the occlusion can be as a key factor to optimize tracking performance.The occlusion-completed is restricted by the target-captured issues temporarily,which is challenged for target tracking.The partial-occluded target is still challenged to be captured because the visual inf ormation of the occluded target is contaminated and the extracted target features are incomplete,and it will cause tracking drift as well.Method To resolve occlusion problem,we develop a low viewpoint-based adaptive occlusion-relevant multiple targets tracking algorithm.The proposed algorithm is composed of three main aspects as following:1)An adaptive anti-occlusion feature is illustrated in terms of the occlusion degree of each frame.To enhance its adaptability for occlusion,global occlusion information is used to adjust feature-related structure dynamically.2)When the occlusion occurs,the target will disappear temporarily.When it reappears again after occlusion,it is often transferred to a new target and the tracking ID switch occurs.Therefore,a cascade screening mechanism is melted into for new target problem-identified.Due to the intensive change of occlusion-based target features,high-level and low-level features are employed both to prevent the virtual phenomenon for new target.3)A large amount of target-occluded noise will be introduced into the template library if they are updated into the template library with no clarification.Therefore,an adaptive anti-interference template upd

关 键 词：多目标跟踪 低视点 遮挡 抗遮挡特征 数据关联 模板更新 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]