Journal article 43229 views 128 downloads
DS-KCF: a real-time tracker for RGB-D data
Journal of Real-Time Image Processing, Volume: 16, Issue: 5, Pages: 1439 - 1458
Swansea University Author: Adeline Paiement
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DOI (Published version): 10.1007/s11554-016-0654-3
Abstract
We propose an RGB-D single-object tracker, built upon the extremely fast RGB-only KCF tracker that is able to exploit depth information to handle scale changes, occlusions, and shape changes. Despite the computational demands of the extra functionalities, we still achieve real-time performance rates...
Published in: | Journal of Real-Time Image Processing |
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ISSN: | 1861-8200 1861-8219 |
Published: |
Springer Science and Business Media LLC
2019
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Online Access: |
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URI: | https://cronfa.swan.ac.uk/Record/cronfa31410 |
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Abstract: |
We propose an RGB-D single-object tracker, built upon the extremely fast RGB-only KCF tracker that is able to exploit depth information to handle scale changes, occlusions, and shape changes. Despite the computational demands of the extra functionalities, we still achieve real-time performance rates of 35–43 fps in MATLAB and 187 fps in our C++ implementation. Our proposed method includes fast depth-based target object segmentation that enables, (1) efficient scale change handling within the KCF core functionality in the Fourier domain, (2) the detection of occlusions by temporal analysis of the target’s depth distribution, and (3) the estimation of a target’s change of shape through the temporal evolution of its segmented silhouette allows. Finally, we provide an in-depth analysis of the factors affecting the throughput and precision of our proposed tracker and perform extensive comparative analysis. Both the MATLAB and C++ versions of our software are available in the public domain. |
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Keywords: |
RGB-D tracking; Correlation filters; Scale and shape changes handling; Occlusion detection; Depth-based segmentation |
College: |
Faculty of Science and Engineering |
Issue: |
5 |
Start Page: |
1439 |
End Page: |
1458 |