Integrated Framework For Single Visual Object Tracking


Ong, Lee Yeng (2019) Integrated Framework For Single Visual Object Tracking. PhD thesis, Multimedia University.

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Visual object tracking is a process that imitates the visual perception of a human eye to observe the dynamic configuration of an object or target in visual surveillance. However, under unconstrained and changing environments, the target of the visual surveillance also undergoes appearance variation as well as vulnerable to distortion effect. The ultimate aim of a visual object tracker not only has to track a single object accurately but also has to maintain the tracking process until the end of the video sequence. This work aims to devise a single-object tracker based on an integrated framework that specifically incorporates four interrelated modules (appearance modelling, motion modelling, object localisation and multi-level scrutiny) to handle appearance variation and distortion effect. Both primary modules, namely appearance and motion modelling establish the global and local features of visual content with the movement information of a target across the consecutive frames. The outcomes of the primary modules are integrated to verify the tracked location of the target in the object localisation module. Lastly, the distortion effect is closely monitored with the multilevel scrutiny approach before selectively update the appearance variation. The approaches that are proposed for each module are elaborated in the following contributions. In the appearance modelling module, two new region descriptors that exploit moment descriptor using the normalisation (GRD) and weighted (LRD) approaches are proposed.

Item Type: Thesis (PhD)
Additional Information: Call No.: TK7882.M68 O54 2019
Uncontrolled Keywords: Motion detectors
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics
Divisions: Faculty of Law (FOL)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 22 Sep 2020 17:06
Last Modified: 22 Sep 2020 17:06


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