Single-target tracking of arbitrary objects using multi-layered features and contextual information

Xiao, Jingjing (2016). Single-target tracking of arbitrary objects using multi-layered features and contextual information. University of Birmingham. Ph.D.

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Abstract

This thesis investigated single-target tracking of arbitrary objects. Tracking is a difficult problem due to a variety of challenges such as significant deformations of the target, occlusions, illumination variations, background clutter and camouflage. To achieve robust tracking performance under these severe conditions, this thesis proposed firstly a novel RGB single-target tracker which models the target with multi-layered features and contextual information. The proposed algorithm was tested on two different tracking benchmarks, i.e., VTB and VOT, where it demonstrated significantly more robust performance than other state-of-the-art RGB trackers. Proposed secondly was an extension of the designed RGB tracker to handle RGB-D images using both temporal and spatial constraints to exploit depth information more robustly. For evaluation, the thesis introduced a new RGB-D benchmark dataset with per-frame annotated attributes and extensive bias analysis, on which the proposed tracker achieved the best results. Proposed thirdly was a new tracking approach to handle camouflage problems in highly cluttered scenes exploiting global dynamic constraints from the context. To evaluate the tracker, a benchmark dataset was augmented with a new set of clutter sub-attributes. Using this dataset, it was demonstrated that the proposed method outperforms other state-of-the-art single target trackers on highly cluttered scenes.

Type of Work:	Thesis (Doctorates > Ph.D.)
Award Type:	Doctorates > Ph.D.
Supervisor(s):	Supervisor(s) Email ORCID Leonardis, Ales UNSPECIFIED UNSPECIFIED Stolkin, Rustam UNSPECIFIED UNSPECIFIED Stone 1958-, Robert J. (Robert John) UNSPECIFIED UNSPECIFIED Oussalah, Mourad UNSPECIFIED UNSPECIFIED
Licence:
College/Faculty:	Colleges (2008 onwards) > College of Engineering & Physical Sciences
School or Department:	School of Engineering, Department of Electronic, Electrical and Systems Engineering
Funders:	None/not applicable
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
URI:	http://etheses.bham.ac.uk/id/eprint/6688

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