中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Multi-technique object tracking approach- A reinforcement paradigm

文献类型:期刊论文

作者Oluwarotimi Williams Samuel; Grace Mojisola Asogbon; Arun Kumar Sangaiah; Guanglin Li
刊名Computers & Electrical Engineering
出版日期2017
文献子类期刊论文
英文摘要In recent years, surveillance is fast becoming an essential part of everyday life in both commercial and residential environments due to the vital role it plays in the society. The existing tracking methods are limited by factors such as illumination variations, occlusions, camera movements, and background clutters among others. Hence, a robust multi-technique tracking method based on continuous adaptive mean shift (CamShift), corrected background weighted histogram, and unscented particle filter techniques is proposed. The mean square error statistic was used to evaluate the performance of the proposed method in terms of correctly estimating the path of a target object in video sequence acquired from three different scenarios. The obtained results showed that our proposed method has a significant improvement both quantitatively and qualitatively across all scenarios compared to the traditional CamShift and some existing methods. The proposed multi-technique approach might potentially improve the tracking capability of surveillance devices.
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语种英语
WOS记录号WOS:000429760300042
源URL[http://ir.siat.ac.cn:8080/handle/172644/11942]  
专题深圳先进技术研究院_医工所
作者单位Computers & Electrical Engineering
推荐引用方式
GB/T 7714
Oluwarotimi Williams Samuel,Grace Mojisola Asogbon,Arun Kumar Sangaiah,et al. Multi-technique object tracking approach- A reinforcement paradigm[J]. Computers & Electrical Engineering,2017.
APA Oluwarotimi Williams Samuel,Grace Mojisola Asogbon,Arun Kumar Sangaiah,&Guanglin Li.(2017).Multi-technique object tracking approach- A reinforcement paradigm.Computers & Electrical Engineering.
MLA Oluwarotimi Williams Samuel,et al."Multi-technique object tracking approach- A reinforcement paradigm".Computers & Electrical Engineering (2017).

入库方式: OAI收割

来源:深圳先进技术研究院

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