Paper Info
Title
Computer Vision Algorithms Acceleration Using Graphic Processors Nvidia Cuda
Abstract
Using graphic processing units (GPUs) in parallel with central processing unit in order to accelerate algorithms and applications demanding extensive computational resources has been a new trend used for the last few years. In this paper, we propose a GPU-accelerated method to parallelize different Computer vision tasks. We will report on parallelism and acceleration in computer vision applications, we provide an overview about the CUDA NVIDIA GPU programming language used. After that we will dive on GPU Architecture and acceleration used for time consuming optimization. We introduce a high-speed computer vision algorithm using graphic processing unit by using the NVIDIA's programming framework compute unified device architecture (CUDA). We realize high and significant accelerations for our computer vision algorithms and we demonstrate that using CUDA as a GPU programming language can improve Efficiency and speedups. Especially we demonstrate the efficiency of our implementations of our computer vision algorithms by speedups obtained for all our implementations especially for some tasks and for some image sizes that come up to 8061 and 5991 and 722 acceleration times.
Year
DOI
Venue
2020
10.1007/s10586-020-03090-6
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
Keywords
DocType
Volume
Computer vision, Integral image, Prefix sum, Features extraction, GPU, NVIDIA CUDA, Image covariance
Journal
23
Issue
ISSN
Citations 
4
1386-7857
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Mouna Afif193.28
Yahia Said2217.09
Mohamed Atri315427.75