Visual adaptive tracking for monocular omnidirectional camera
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 253-262 |
Journal / Publication | Journal of Visual Communication and Image Representation |
Volume | 55 |
Online published | 18 Jun 2018 |
Publication status | Published - Aug 2018 |
Link(s)
Abstract
This paper presents a sophisticated patch-based visual tracking algorithm using an omnidirectional camera with distortion adaptation. The omnidirectional camera is modeled using the equivalent projection theory, so that a nonlinear deformed neighbourhood can be accurately estimated in the image plane, which significantly facilitates feature coding. In order to improve the omnidirectional tracking performance, a patch-based multi-feature matching method is proposed under a probability framework. In particular, the distributions of patches covering key parts of the target are weighted adaptively according to their joint-feature response, which is able to track target robustly and filter out the outliers effectively. Extensive experiments have been conducted to verify the performance of the proposed omnidirectional tracking algorithm, which obtains promising results on challenging datasets and outperforms many state-of-the-art methods.
Research Area(s)
- Multi-feature integration, Omnidirectional camera, Visual tracking
Citation Format(s)
Visual adaptive tracking for monocular omnidirectional camera. / Tang, Yazhe; Gao, Zhi; Lin, Feng; Li, Y.F.; Wen, Fei.
In: Journal of Visual Communication and Image Representation, Vol. 55, 08.2018, p. 253-262.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review