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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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Keep updated to our software releases, new publications and videos by subscribing to our news feed and youtube channel: |
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NEWS |
| 2009-11-09 |
New Publication Online: Local, Semi-global, and Global Optimization for Motion Estimation |
| Link | This PhD thesis on optical flow is written by our fellow researcher Werner Trobin. |
| 2009-11-02 |
New Publication Online: A Variational Approach to Semiautomatic Generation of Digital Terrain Models (preprint) |
| Link | This work will be presented at the 5th International Symposium on Visual Computing in Las Vegas, USA |
| 2009-10-02 |
Software Update: FlowLib; New Software available: FlowLibGui |
| Link | Update of our FlowLib package. This package supports Cuda 2.3 on Linux x64 and Windows XP 32bit. This version of the FlowLib was used for the demos at ICCV09 and NVIDIAs GTC 2009. Please note that from now on we also provide a GUI application as separate package to make it easy to play around with our optical flow algorithm. |
| 2009-08-12 |
New Publication Online: Tracking as Segmentation of Spatial-Temporal Volumes by Anisotropic Weighted TV |
| Link | This work will be presented at the EMMCVPR in Bonn, Germany |
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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.
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 Google Analytics Disclaimer: This website uses Google Analytics, a web analytics service provided by Google, Inc. ("Google"). Google Analytics uses "cookies", which are text files placed on your computer, to help the website analyze how users use the site. The information generated by the cookie about your use of the website (including your IP address) will be transmitted to and stored by Google on servers in the United States . Google will use this information for the purpose of evaluating your use of the website, compiling reports on website activity for website operators and providing other services relating to website activity and internet usage. Google may also transfer this information to third parties where required to do so by law, or where such third parties process the information on Google's behalf. Google will not associate your IP address with any other data held by Google. You may refuse the use of cookies by selecting the appropriate settings on your browser, however please note that if you do this you may not be able to use the full functionality of this website. By using this website, you consent to the processing of data about you by Google in the manner and for the purposes set out above.
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