Robust Visual Tracking Based on Convex Hull with EMD-L1
- Autores: Wang J.1,2, Wang Y.1,2, Deng C.1,2, Wang S.1,2
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Afiliações:
- Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing
- School of Information Engineering
- Edição: Volume 28, Nº 1 (2018)
- Páginas: 44-52
- Seção: Representation, Processing, Analysis, and Understanding of Images
- URL: https://bakhtiniada.ru/1054-6618/article/view/195290
- DOI: https://doi.org/10.1134/S1054661818010078
- ID: 195290
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Resumo
Factors such as drastic illumination variations, partial occlusion, rotation make robust visual tracking a difficult problem. Some tracking algorithms represent a target appearances based on obtained tracking results from previous frames with a linear combination of target templates. This kind of target representation is not robust to drastic appearance variations. In this paper, we propose a simple and effective tracking algorithm with a novel appearance model. A target candidate is represented by convex combinations of target templates. Measuring the similarity between a target candidate and the target templates is a key problem for a robust likelihood evaluation. The distance between a target candidate and the templates is measured using the earth mover’s distance with L1 ground distance. Comprehensive experiments demonstrate the robustness and effectiveness of the proposed tracking algorithm against state-of-the-art tracking algorithms.
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Sobre autores
Jun Wang
Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing; School of Information Engineering
Email: dengchengzhi@126.com
República Popular da China, Nanchang, 330099; Nanchang, 330099
Yuanyun Wang
Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing; School of Information Engineering
Email: dengchengzhi@126.com
República Popular da China, Nanchang, 330099; Nanchang, 330099
Chengzhi Deng
Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing; School of Information Engineering
Autor responsável pela correspondência
Email: dengchengzhi@126.com
República Popular da China, Nanchang, 330099; Nanchang, 330099
Shengqian Wang
Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing; School of Information Engineering
Email: dengchengzhi@126.com
República Popular da China, Nanchang, 330099; Nanchang, 330099
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