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Real-time object detection on CUDA

Adam Herout, Radovan Josth, Roman Juranek, Jiri Havel, Michal Hradis, Pavel Zemcik
Graph@FIT, Brno University of Technology, Bozetechova 2, 616 00 Brno, Czech Republic
Journal of Real-Time Image Processing (8 October 2010), pp. 1-12.

@article{heroutreal,

   title={Real-time object detection on CUDA},

   author={Herout, A. and Jo{v{s}}th, R. and Jur{‘a}nek, R. and Havel, J. and Hradi{v{s}}, M. and Zem{v{c}}{‘i}k, P.},

   journal={Journal of Real-Time Image Processing},

   pages={1–12},

   issn={1861-8200},

   publisher={Springer}

}

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The aim of the research described in this article is to accelerate object detection in images and video sequences using graphics processors. It includes algorithmic modifications and adjustments of existing detectors, constructing variants of efficient implementations and evaluation comparing with efficient implementations on the CPUs. This article focuses on detection by statistical classifiers based on boosting. The implementation and the necessary algorithmic alterations are described, followed by experimental measurements of the created object detector and discussion of the results. The final solution outperforms the reference efficient CPU/SSE implementation, by approximately 6-8x
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