Publication Details
Real-time object detection on CUDA
Jošth Radovan, Ing., Ph.D.
Juránek Roman, Ing., Ph.D. (DCGM)
Havel Jiří, Ing., Ph.D. (CM-SFE)
Hradiš Michal, Ing., Ph.D. (DCGM)
Zemčík Pavel, prof. Dr. Ing., dr. h. c. (DCGM)
Object detection, Pattern recognition, Acceleration, CUDA, AdaBoost
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 6-89 for high-resolution videos using nVidia GeForce 9800GTX and Intel Core2 Duo E8200.
@article{BUT50548,
author="Adam {Herout} and Radovan {Jošth} and Roman {Juránek} and Jiří {Havel} and Michal {Hradiš} and Pavel {Zemčík}",
title="Real-time object detection on CUDA",
journal="Journal of Real-Time Image Processing",
year="2011",
volume="2011",
number="3",
pages="159--170",
issn="1861-8200",
url="http://www.springerlink.com/content/n44j1g424487781k/fulltext.pdf"
}