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Object Tracking Using Multiple Features and Adaptive Model Updating

文献类型：期刊论文

作者Hu, Qingyong1; Guo, Yulan1,2; Lin, Zaiping1; An, Wei1; Cheng, Hongwei1
刊名IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
出版日期2017-11-01
卷号66期号:11页码:2882-2897
关键词Adaptive model updating correlation filters multiple feature integration object tracking
ISSN号0018-9456
DOI10.1109/TIM.2017.2729378
英文摘要Correlation filter-based tracking methods have been intensively investigated for their high efficiency and robustness. However, a single feature-based tracker cannot adapt to challenging situations, such as severe deformation, rotation, and illumination variations. Besides, a simple linear interpolation-based model updating mechanism is prone to model degradation, and consequently tracker drifting. In this paper, a 2-D location filter is combined with a 1-D scale filter to jointly estimate the state of object under tracking, and three complementary features are integrated to further enhance the overall tracking performance. Besides, we define a penalty factor for adaptive model updating, to achieve a balance between stability and flexibility, especially when the object is under occlusion. Extensive experiments have been conducted on four large-scale data sets, namely, the object tracking benchmark, VOT15, Temple-Color128, and the UAV123 tracking benchmark. Quantitative and qualitative results show that our proposed tracker achieves promising results in terms of tracking accuracy, robustness, and speed as compared with other popular trackers, and is highly suitable for real-time applications, such as unmanned aerial vehicles. It outperforms the state-of-the-art methods under different nuisances, including scale variation, deformation, occlusion, rotation, and out-of-view.
资助项目National Natural Science Foundation of China[61602499] ; National Natural Science Foundation of China[61471371] ; National Postdoctoral Program for Innovative Talents[BX201600172] ; China Postdoctoral Science Foundation
WOS研究方向Engineering ; Instruments & Instrumentation
语种英语
WOS记录号WOS:000412573300010
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
源URL[http://119.78.100.204/handle/2XEOYT63/6781]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Guo, Yulan
作者单位1.Natl Univ Def Technol, Coll Elect Sci & Engn, Changsha 410073, Hunan, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, Beijing 100080, Peoples R China
推荐引用方式
GB/T 7714		 Hu, Qingyong,Guo, Yulan,Lin, Zaiping,et al. Object Tracking Using Multiple Features and Adaptive Model Updating[J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT,2017,66(11):2882-2897.
APA Hu, Qingyong,Guo, Yulan,Lin, Zaiping,An, Wei,&Cheng, Hongwei.(2017).Object Tracking Using Multiple Features and Adaptive Model Updating.IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT,66(11),2882-2897.
MLA Hu, Qingyong,et al."Object Tracking Using Multiple Features and Adaptive Model Updating".IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 66.11(2017):2882-2897.

入库方式： OAI收割

来源：计算技术研究所

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