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Thermo-visual feature fusion for object tracking using multiple spatiogram trackers

Ó Conaire, Ciarán and O'Connor, Noel E. and Smeaton, Alan F. (2007) Thermo-visual feature fusion for object tracking using multiple spatiogram trackers. Machine Vision and Applications . ISSN 1432-1769

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In this paper, we propose a framework that can efficiently combine features for robust tracking based on fusing the outputs of multiple spatiogram trackers. This is achieved without the exponential increase in storage and processing that other multimodal tracking approaches suffer from. The framework allows the features to be split arbitrarily between the trackers, as well as providing the flexibility to add, remove or dynamically weight features. We derive a mean-shift type algorithm for the framework that allows efficient object tracking with very low computational overhead. We especially target the fusion of thermal infrared and visible spectrum features as the most useful features for automated surveillance applications. Results are shown on multimodal video sequences clearly illustrating the benefits of combining multiple features using our framework.

Item Type:Article (Published)
Additional Information:Special Issue Paper. The original publication is available at
Uncontrolled Keywords:Thermal infrared; visible spectrum; fusion; tracking; spatiogram;
Subjects:Physical Sciences > Optoelectronics
Computer Science > Digital video
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Digital Video Processing (CDVP)
Research Initiatives and Centres > Adaptive Information Cluster (AIC)
Publisher:Springer Berlin / Heidelberg
Official URL:
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland, SFI 03/IN.3/I361, Irish Research Council for Science Engineering and Technology
ID Code:206
Deposited On:04 Mar 2008 by DORAS Administrator. Last Modified 05 May 2010 12:33

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