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Sensors 2016, 16(7), 949; doi:10.3390/s16070949

Real-Time Visual Tracking through Fusion Features

Key Laboratory of Precision Opto-Mechatronics Technology of Ministry of Education, Beihang University, Beijing 100191, China
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Academic Editor: Vittorio M. N. Passaro
Received: 19 April 2016 / Revised: 16 June 2016 / Accepted: 16 June 2016 / Published: 23 June 2016
(This article belongs to the Section Physical Sensors)
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Abstract

Due to their high-speed, correlation filters for object tracking have begun to receive increasing attention. Traditional object trackers based on correlation filters typically use a single type of feature. In this paper, we attempt to integrate multiple feature types to improve the performance, and we propose a new DD-HOG fusion feature that consists of discriminative descriptors (DDs) and histograms of oriented gradients (HOG). However, fusion features as multi-vector descriptors cannot be directly used in prior correlation filters. To overcome this difficulty, we propose a multi-vector correlation filter (MVCF) that can directly convolve with a multi-vector descriptor to obtain a single-channel response that indicates the location of an object. Experiments on the CVPR2013 tracking benchmark with the evaluation of state-of-the-art trackers show the effectiveness and speed of the proposed method. Moreover, we show that our MVCF tracker, which uses the DD-HOG descriptor, outperforms the structure-preserving object tracker (SPOT) in multi-object tracking because of its high-speed and ability to address heavy occlusion. View Full-Text
Keywords: visual tracking; fusion feature; correlation filters visual tracking; fusion feature; correlation filters
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Ruan, Y.; Wei, Z. Real-Time Visual Tracking through Fusion Features. Sensors 2016, 16, 949.

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