ABOUT

GPU4Vision is a project founded by the Institute for Computer Graphics and Vision, Graz University of Technology. We'd like to make cutting edge research results in the field of GPU-based vision algorithms publicly available. We use Nvidia consumer graphics cards and their CUDA framework. More...

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NEWS

2012-05-15 New Publication Online: Joint Motion Estimation and Segmentation of Complex Scenes with Label Costs and Occlusions
Link This work will be presented at CVPR 2012, Providence, Rhode Island
 
2012-05-15 New Publication Online: Pushing the Limits of Stereo Using Variational Stereo Estimation
Link This work will be presented at the IEEE Intelligent Vehicles Symposium 2012
 
2012-05-15 New Code Online: Primal Dual-GUI
Link A graphical matlab toolbox that implements several models. Includes optical flow, segmentation, denoising, zooming, inpainting and deconvolution.
 
2011-07-22 New Publication Online: Global Relabeling for Continuous Optimization in Binary Image Segmentation
Link This work will be presented at the 8th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition in Saint Petersburg, Russia.
 

Previous news entries...

 

WHY GPUS?

Consumer graphics adapters have evolved from petite units with very limited general applicability to high-power computational devices, which are very flexible in terms of their usage. Their computational power and memory bandwith undertook vast increases during the last years. Offering high-level-language support, recent graphics hardware is able to outperform CPU clusters in a wide range of applications.

Computational Power Memory Bandwidth Computational Efficiency
Overview: Computational power, memory bandwith and efficiency of recent Nvidia GPUs compared to recent Intel desktop CPUs. (click to enlarge)

Modern graphics cards are highly parallel computational devices with fast shared memory. This allows for solving problems with high arithmetic density in realtime, which would take several minutes computed on CPUs. Computer vision problems usually fit perfectly to the architecture of modern graphics hardware, as beeing parallelizable and requiring plenty of operations on each pixel and its surroundings.

IMPRINT

Institute for Computer Graphics and Vision
Graz University of Technology
Inffeldgasse 16/II
A-8010 Graz, Austria
www.icg.tugraz.at

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