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01-07-2019 | REPRESENTATION, PROCESSING, ANALYSIS, AND UNDERSTANDING OF IMAGES | Issue 3/2019

Pattern Recognition and Image Analysis 3/2019

Robust Visual Tracking Based on Relaxed Target Representation

Journal:
Pattern Recognition and Image Analysis > Issue 3/2019
Author:
Yuanyun Wang
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Yuanyun Wang is an Assistant Professor in the School of Information Engineering at Nanchang Institute of Technology, China. She received the B.S. and M.S. degrees in Computer Science and Technology from Nanchang University, China in 2004 and 2007 respectively. Her research interests include visual tracking and pattern recognition.

Abstract

Developing an effective target appearance model is a challenging task in visual tracking under the influences of complicated appearance variations. Many tracking algorithms use a linear combination of previous tracking results to represent a target candidate. In existing target representations, all of the feature elements of a target candidate have the same coding vector. With such type of target representations, robust tracking is not satisfactory when drastic appearance variations occur. In this work, we present a novel appearance model for visual tracking. The proposed appearance model considers the similarity and the distinctiveness of the feature elements of a target candidate. The feature elements should share some similarity to jointly represent a target pattern. We exploit the distinctiveness of feature elements to represent the different importance by introducing a weighted regularization term in the appearance model. A more stable and discriminative target representation is obtained. Superior performance on challenging sequences against state-of-the-art trackers show the robustness of the novel appearance model and the proposed tracker.

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