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2008

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

8 years 9 months ago
Thermo-visual feature fusion for object tracking using multiple spatiogram trackers
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. Keywords Thermal infrared
Ciarán O Conaire, Noel E. O'Connor, Alan F.
Added 14 Dec 2010
Updated 14 Dec 2010
Type Journal
Year 2008
Where MVA
Authors Ciarán O Conaire, Noel E. O'Connor, Alan F. Smeaton
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