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Sensors 2017, 17(3), 433; doi:10.3390/s17030433

Effective Visual Tracking Using Multi-Block and Scale Space Based on Kernelized Correlation Filters

Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University, Seoul 06974, Korea
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Academic Editor: Joonki Paik
Received: 9 December 2016 / Revised: 13 February 2017 / Accepted: 17 February 2017 / Published: 23 February 2017
(This article belongs to the Special Issue Video Analysis and Tracking Using State-of-the-Art Sensors)
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Abstract

Accurate scale estimation and occlusion handling is a challenging problem in visual tracking. Recently, correlation filter-based trackers have shown impressive results in terms of accuracy, robustness, and speed. However, the model is not robust to scale variation and occlusion. In this paper, we address the problems associated with scale variation and occlusion by employing a scale space filter and multi-block scheme based on a kernelized correlation filter (KCF) tracker. Furthermore, we develop a more robust algorithm using an appearance update model that approximates the change of state of occlusion and deformation. In particular, an adaptive update scheme is presented to make each process robust. The experimental results demonstrate that the proposed method outperformed 29 state-of-the-art trackers on 100 challenging sequences. Specifically, the results obtained with the proposed scheme were improved by 8% and 18% compared to those of the KCF tracker for 49 occlusion and 64 scale variation sequences, respectively. Therefore, the proposed tracker can be a robust and useful tool for object tracking when occlusion and scale variation are involved. View Full-Text
Keywords: computer vision; visual tracking; scale variation; correlation filter; multi-block method; adaptive learning rate; illumination variation; partial occlusion computer vision; visual tracking; scale variation; correlation filter; multi-block method; adaptive learning rate; illumination variation; partial occlusion
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Jeong, S.; Kim, G.; Lee, S. Effective Visual Tracking Using Multi-Block and Scale Space Based on Kernelized Correlation Filters. Sensors 2017, 17, 433.

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