Combining Color Features for Real-Time Correlation Tracking
Correlation filter-based approaches achieve competitive results in visual tracking, but the traditional correlation tracking methods failed in mining the color information of the videos. To address this issue, we propose a novel tracker combined with color features in a correlation filter framework,...
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| Veröffentlicht in: | IEICE Transactions on Information and Systems 2017/01/01, Vol.E100.D(1), pp.225-228 |
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| container_title | IEICE Transactions on Information and Systems |
| container_volume | E100.D |
| creator | XU, Yulong MIAO, Zhuang WANG, Jiabao LI, Yang LI, Hang ZHANG, Yafei XU, Weiguang PAN, Zhisong |
| description | Correlation filter-based approaches achieve competitive results in visual tracking, but the traditional correlation tracking methods failed in mining the color information of the videos. To address this issue, we propose a novel tracker combined with color features in a correlation filter framework, which extracts not only gray but also color information as the feature maps to compute the maximum response location via multi-channel correlation filters. In particular, we modify the label function of the conventional classifier to improve positioning accuracy and employ a discriminative correlation filter to handle scale variations. Experiments are performed on 35 challenging benchmark color sequences. And the results clearly show that our method outperforms state-of-the-art tracking approaches while operating in real-time. |
| doi_str_mv | 10.1587/transinf.2016EDL8053 |
| format | Article |
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Inf. & Syst.</addtitle><date>2017-01-01</date><risdate>2017</risdate><volume>E100.D</volume><issue>1</issue><spage>225</spage><epage>228</epage><pages>225-228</pages><issn>0916-8532</issn><eissn>1745-1361</eissn><abstract>Correlation filter-based approaches achieve competitive results in visual tracking, but the traditional correlation tracking methods failed in mining the color information of the videos. To address this issue, we propose a novel tracker combined with color features in a correlation filter framework, which extracts not only gray but also color information as the feature maps to compute the maximum response location via multi-channel correlation filters. In particular, we modify the label function of the conventional classifier to improve positioning accuracy and employ a discriminative correlation filter to handle scale variations. Experiments are performed on 35 challenging benchmark color sequences. 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| identifier | ISSN: 0916-8532 |
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| issn | 0916-8532 1745-1361 |
| language | eng |
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| source | J-STAGE (Japan Science & Technology Information Aggregator, Electronic) Freely Available Titles - Japanese; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
| subjects | Color color feature Correlation correlation filter Data mining Feature extraction Feature maps Optical tracking Position (location) Real time real-time visual tracking Tracking Tracking (position) |
| title | Combining Color Features for Real-Time Correlation Tracking |
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