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融合GMS检测和置信度判别的TLD目标跟踪
引用本文:郭伟,杨琛,曲海成,邢宇哲. 融合GMS检测和置信度判别的TLD目标跟踪[J]. 激光与光电子学进展, 2021, 58(4): 155-166
作者姓名:郭伟  杨琛  曲海成  邢宇哲
作者单位:辽宁工程技术大学软件学院,辽宁葫芦岛125105
基金项目:国家自然科学基金(41701479);辽宁省自然科学基金(20180550529)。
摘    要:针对目标在遮挡、尺度变化等复杂场景下易产生模型漂移问题,基于跟踪学习检测(TLD)框架提出一种结合基于网格的运动统计(GMS)检测和置信度判别的长时目标跟踪算法.首先在跟踪模块中采用快速判别尺度空间的相关滤波器(fDSST)作为跟踪器,利用位置滤波器和尺度滤波器对上一帧目标进行位置与尺度的判别,并依据TLD算法中跟踪模...

关 键 词:图像处理  目标跟踪  模型漂移  运动统计  动态缩减

TLD Target Tracking Fused with GMS Detection and Confidence Discrimination
Guo Wei,Yang Chen,Qu Haicheng,Xing Yuzhe. TLD Target Tracking Fused with GMS Detection and Confidence Discrimination[J]. Laser & Optoelectronics Progress, 2021, 58(4): 155-166
Authors:Guo Wei  Yang Chen  Qu Haicheng  Xing Yuzhe
Affiliation:(School of Software,Liaoning Technical University,Huludao,Liaoning 125105,China)
Abstract:In order to solve the problem of model drift in complex scenes such as occlusion and scale variation,this paper proposes a long-term target tracking algorithm based on TLD framework,which integrates GMS detection and confidence discrimination.First,in tracking module,the fast discriminating scale space correlation filter(fDSST)is used as the tracker,and the position filter and scale filter are used to distinguish the position and scale of the target in the previous frame.According to the independence of the tracking module and the detection module in the TLD algorithm,the results of the tracking module are input into the detection module,and the average peak-to-correlation energy(APCE)is used to determine the template update to judge the confidence.In the detection module,GMS grid motion statistics is used as the detector to make the ORB algorithm with fast rotation invariance feature to match the target in the previous frame,and then the grid motion statistics is used to filter the matching results to achieve the rough positioning of the target position,and the target detection area is reduced dynamically according to the prediction position.Finally,the cascaded classifier is used to locate the target accurately.The results show that the tracking method proposed in this paper can greatly improve the tracking speed of the algorithm while effectively preventing model drift,and has better accuracy and robustness to challenging environments such as target occlusion,scale variation and rotation.
Keywords:image processing  target tracking  model drift  motion statistics  dynamic cutting
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