Scale Adaptive Kernelized Correlation Filter Tracker with Feature Fusion
Joint Authors
Zhou, Tongxue
Zhu, Ming
Zeng, Dongdong
Yang, Hang
Source
Mathematical Problems in Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-10-17
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Visual tracking is one of the most important components in numerous applications of computer vision.
Although correlation filter based trackers gained popularity due to their efficiency, there is a need to improve the overall tracking capability.
In this paper, a tracking algorithm based on the kernelized correlation filter (KCF) is proposed.
First, fused features including HOG, color-naming, and HSV are employed to boost the tracking performance.
Second, to tackle the fixed template size, a scale adaptive scheme is proposed which strengthens the tracking precision.
Third, an adaptive learning rate and an occlusion detection mechanism are presented to update the target appearance model in presence of occlusion problem.
Extensive evaluation on the OTB-2013 dataset demonstrates that the proposed tracker outperforms the state-of-the-art trackers significantly.
The results show that our tracker gets a 14.79% improvement in success rate and a 7.43% improvement in precision rate compared to the original KCF tracker, and our tracker is robust to illumination variations, scale variations, occlusion, and other complex scenes.
American Psychological Association (APA)
Zhou, Tongxue& Zhu, Ming& Zeng, Dongdong& Yang, Hang. 2017. Scale Adaptive Kernelized Correlation Filter Tracker with Feature Fusion. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1189594
Modern Language Association (MLA)
Zhou, Tongxue…[et al.]. Scale Adaptive Kernelized Correlation Filter Tracker with Feature Fusion. Mathematical Problems in Engineering No. 2017 (2017), pp.1-8.
https://search.emarefa.net/detail/BIM-1189594
American Medical Association (AMA)
Zhou, Tongxue& Zhu, Ming& Zeng, Dongdong& Yang, Hang. Scale Adaptive Kernelized Correlation Filter Tracker with Feature Fusion. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1189594
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1189594