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A novel background-weighted histogram scheme based on foreground saliency for mean-shift tracking

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成果类型:
期刊论文
作者:
Wang, Dejun;Sun, Weiping*;Yu, Shengsheng;Li, Lin;Liu, Wei
通讯作者:
Sun, Weiping
作者机构:
[Li, Lin; Wang, Dejun; Sun, Weiping; Yu, Shengsheng; Liu, Wei] Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Wuhan 430074, Peoples R China.
[Wang, Dejun] Donghua Software Co Ltd, Beijing 100190, Peoples R China.
[Li, Lin] Wuhan Univ Technol, Sch Comp Sci & Technol, Wuhan 430070, Peoples R China.
[Liu, Wei] Cent China Normal Univ, Sch Comp Sci, Wuhan 430079, Peoples R China.
通讯机构:
[Sun, Weiping] H
Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Wuhan 430074, Peoples R China.
语种:
英文
关键词:
Target tracking;Mean-Shift;Weighted histogram;Foreground feature saliency
期刊:
Multimedia Tools and Applications
ISSN:
1380-7501
年:
2016
卷:
75
期:
17
页码:
10271-10289
基金类别:
National Natural Science Foundation of China (NSFC)National Natural Science Foundation of China (NSFC) [61300140]
机构署名:
本校为其他机构
院系归属:
计算机学院
摘要:
Effective appearance models are one critical factor for robust object tracking. In this paper, we introduce foreground feature saliency concept into the background modelling, and put forward a novel foreground saliency-based background-weighted histogram scheme (FSBWH) for target representation and tracking, which exploits salient features from both foreground and background. We think that background and foreground salient features are both crucial for target representation and tracking. Experimental results show that the proposed FSBWH scheme can improve the robustness and performance of trac...

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