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Adaptive detection and tracking using multimodal information

Ó Conaire, Ciarán (2007) Adaptive detection and tracking using multimodal information. PhD thesis, Dublin City University.

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Abstract

This thesis describes work on fusing data from multiple sources of information, and focuses on two main areas: adaptive detection and adaptive object tracking in automated vision scenarios. The work on adaptive object detection explores a new paradigm in dynamic parameter selection, by selecting thresholds for object detection to maximise agreement between pairs of sources. Object tracking, a complementary technique to object detection, is also explored in a multi-source context and an efficient framework for robust tracking, termed the Spatiogram Bank tracker, is proposed as a means to overcome the difficulties of traditional histogram tracking. As well as performing theoretical analysis of the proposed methods, specific example applications are given for both the detection and the tracking aspects, using thermal infrared and visible spectrum video data, as well as other multi-modal information sources.

Item Type:Thesis (PhD)
Date of Award:November 2007
Refereed:No
Supervisor(s):O'Connor, Noel E.
Subjects:Engineering > Imaging systems
Engineering > Electronics
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Digital Video Processing (CDVP)
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 3.0 License. View License
ID Code:90
Deposited On:13 Dec 2007 by DORAS Administrator. Last Modified 30 Jan 2009 14:25

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