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Accelerating Template-Based Matching on the GPU for AR Applications

Yannick Allusse, Raphael Grasset, Mark Billinghurst
HIT Lab NZ, University of Canterbury, Private Bag 4800, Christchurch, New Zealand
ISMAR ’07 Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality

@conference{allusse2008accelerating,

   title={Accelerating Template-Based Matching on the GPU for AR Applications},

   author={Allusse, Y. and Grasset, R. and Billinghurst, M.},

   booktitle={Mixed and Augmented Reality, 2007. ISMAR 2007. 6th IEEE and ACM International Symposium on},

   pages={271–272},

   year={2008},

   organization={IEEE}

}

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Recently researchers have shown that it is possible to use GPU hardware for image processing and computer vision algorithms. We have been exploring how to use GPU hardware to improve marker-based tracking for AR Applications. In this paper we describe our findings and explored issues in the context of a standard fiducial tracking pipeline. We demonstrate the implementation of a template matching process on the GPU and the performance improvement gained in comparison to a traditional CPU implementation.
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