Book ChapterDOI
Real-Time image processing using graphics hardware: a performance study
Minglun Gong,Aaron Langille,Mingwei Gong +2 more
- pp 1217-1225
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TLDR
This paper quantifies the performance gain that can be achieved by using the GPU for different image processing operations under different conditions and compares the strengths and weaknesses of two of the current leaders in mainstream GPUs – ATI's Radeon and nVidia's GeForce FX.Abstract:
Programmable graphics hardware have proven to be a powerful resource for general computing. Previous research has shown that using a GPU for local image processing operations can be much faster than using a CPU. The actual speedup obtained is influenced by many factors. In this paper, we quantify the performance gain that can be achieved by using the GPU for different image processing operations under different conditions. We also compare the strengths and weaknesses of two of the current leaders in mainstream GPUs – ATI's Radeon and nVidia's GeForce FX. Many interesting observations are obtained through the evaluation.read more
Citations
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GPU-based Video Feature Tracking And Matching
TL;DR: Novel implementations of the KLT feature track- ing and SIFT feature extraction algorithms that run on the graphics processing unit (GPU) and is suitable for video analysis in real-time vision systems.
Journal ArticleDOI
Feature tracking and matching in video using programmable graphics hardware
TL;DR: Novel implementations of the KLT feature tracking and SIFT feature extraction algorithms that run on the graphics processing unit (GPU) and is suitable for video analysis in real-time vision systems are described.
Journal ArticleDOI
Similarity-based image organization and browsing using multi-resolution self-organizing map
Grant Strong,Minglun Gong +1 more
TL;DR: An algorithm is presented in this paper to facilitate the exploration of large image collections based on visual similarities using a self-organizing map which maps high-dimensional feature vectors onto a 2D canvas so that images with similar feature vectors are grouped together.
Journal ArticleDOI
A Unified Graphics and Vision Processor With a 0.89 /spl mu/W/fps Pose Estimation Engine for Augmented Reality
Jae-Sung Yoon,Jeong-Hyun Kim,Hyo-Eun Kim,Won-Young Lee,Seok-Hoon Kim,Kyusik Chung,Jun-Seok Park,Lee-Sup Kim +7 more
TL;DR: A unified vision and graphics processor with three layers is shown to provide a fast pipeline for augmented reality, which is 39% faster than a comparable smartphone implementation.
Journal ArticleDOI
A fast deconvolution-based approach for single-image super-resolution with GPU acceleration
TL;DR: This paper provides a novel and efficient deconvolution method which combines the gradient consistency in images with the anisotropic regularization which has been used in motion deblurring to produce a directly parallelizable solution suitable for running on GPU by minimizing redundancy in computing.
References
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Proceedings ArticleDOI
Multi-resolution real-time stereo on commodity graphics hardware
Ruigang Yang,Marc Pollefeys +1 more
TL;DR: An important advantage of the approach is that rectification is not necessary so that correspondences can just as easily be obtained for images that contain the epipoles, and can easily be extended to multi-baseline stereo.
Proceedings ArticleDOI
The FFT on a GPU
Kenneth Moreland,Edward Angel +1 more
TL;DR: A system that can synthesize an image by conventional means, perform the FFT, filter the image, and finally apply the inverse FFT in well under 1 second for a 512 by 512 image is demonstrated.
Proceedings ArticleDOI
Physically-based visual simulation on graphics hardware
TL;DR: In this paper, the authors present a method for real-time visual simulation of diverse dynamic phenomena using programmable graphics hardware, using an extension of cellular automata known as the coupled map lattice.
Journal ArticleDOI
Fast image segmentation and smoothing using commodity graphics hardware
Ruigang Yang,Greg Welch +1 more
TL;DR: Preliminary results show a performance increase of over 30% using an nVidia GeForce4 when compared to an implementation using Intel MMX optimized code on a 2.2 Ghz Intel P4 CPU.
Proceedings Article
Fast and Accurate Color Images Processing Using 3D Graphics Cards.
TL;DR: It is shown that the GPU can be 10 times faster than the best CPU that has been tested in the case of per-pixel processing with mathematical complex functions and vectorial calculations.