8 May 2017 Log-polar mapping-based scale space tracking with adaptive target response
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Abstract
Correlation filter-based tracking has exhibited impressive robustness and accuracy in recent years. Standard correlation filter-based trackers are restricted to translation estimation and equipped with fixed target response. These trackers produce an inferior performance when encountered with a significant scale variation or appearance change. We propose a log-polar mapping-based scale space tracker with an adaptive target response. This tracker transforms the scale variation of the target in the Cartesian space into a shift along the logarithmic axis in the log-polar space. A one-dimensional scale correlation filter is learned online to estimate the shift along the logarithmic axis. With the log-polar representation, scale estimation is achieved accurately without a multiresolution pyramid. To achieve an adaptive target response, a variance of the Gaussian function is computed from the response map and updated online with a learning rate parameter. Our log-polar mapping-based scale correlation filter and adaptive target response can be combined with any correlation filter-based trackers. In addition, the scale correlation filter can be extended to a two-dimensional correlation filter to achieve joint estimation of the scale variation and in-plane rotation. Experiments performed on an OTB50 benchmark demonstrate that our tracker achieves superior performance against state-of-the-art trackers.
© 2017 SPIE and IS&T
Dong Dong Li, Dong Dong Li, Gongjian Wen, Gongjian Wen, Yangliu Kuai, Yangliu Kuai, Ximing Zhang, Ximing Zhang, } "Log-polar mapping-based scale space tracking with adaptive target response," Journal of Electronic Imaging 26(3), 033003 (8 May 2017). https://doi.org/10.1117/1.JEI.26.3.033003 . Submission: Received: 22 December 2016; Accepted: 13 April 2017
Received: 22 December 2016; Accepted: 13 April 2017; Published: 8 May 2017
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