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Title: Single-target tracking of arbitrary objects using multi-layered features and contextual information
Author: Xiao, Jingjing
ISNI:       0000 0004 5923 8929
Awarding Body: University of Birmingham
Current Institution: University of Birmingham
Date of Award: 2016
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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.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: TK Electrical engineering. Electronics Nuclear engineering