Detail publikace
Real-time object detection on CUDA
Originální název
Real-time object detection on CUDA
Anglický název
Real-time object detection on CUDA
Jazyk
en
Originální abstrakt
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.
Anglický abstrakt
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.
BibTex
@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",
annote="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.",
address="NEUVEDEN",
chapter="50548",
edition="NEUVEDEN",
howpublished="print",
institution="NEUVEDEN",
number="3",
volume="2011",
year="2011",
month="august",
pages="159--170",
publisher="NEUVEDEN",
type="journal article - other"
}