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Real-time object detection on CUDA

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Abstract

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 6–8× for high-resolution videos using nVidia GeForce 9800GTX and Intel Core2 Duo E8200.

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Acknowledgments

This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic under the research program LC-06008 (Center for Computer Graphics) and by the research project “Security-Oriented Research in Information Technology” CEZMSMT, MSM0021630528.

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Authors and Affiliations

  1. Graph@FIT, Brno University of Technology, Bozetechova 2, 616 00, Brno, Czech Republic

    Adam Herout, Radovan Jošth, Roman Juránek, Jiří Havel, Michal Hradiš & Pavel Zemčík

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  1. Adam Herout
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  2. Radovan Jošth
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  3. Roman Juránek
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  4. Jiří Havel
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  5. Michal Hradiš
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  6. Pavel Zemčík
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Correspondence to Adam Herout.

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Herout, A., Jošth, R., Juránek, R. et al. Real-time object detection on CUDA. J Real-Time Image Proc 6, 159–170 (2011). https://doi.org/10.1007/s11554-010-0179-0

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