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Product Info
Additional Info
- Software Development Tools
Programming CUDA-enabled GPUs
- NVIDIA CUDA
- Webinars
Learn more about GPU computing and CUDA-enabled applications through these webinars
- Request Resource CD
If you are new to GPU computing or would like to add to your knowledge of NVIDIA CUDA programming and Tesla hardware then this resource CD is for you.
Relevant Links
Imaging and Computer Vision
Computer vision and image processing algorithms are computationally intensive. With CUDA acceleration, applications can achieve interactive video frame-rate performance. Here we outline some of the work in the area of imaging and vision and point to some resources for developers.
| ISV/Application | Supported Features | Expected Speed up* | Release Status |
| Axxon Intellect | In Development |
* Expected Speed Up vs a quad-core x64 CPU based system. Speed-ups as per NVIDIA in house testing or application provider documentation.
Technical Reports on using CUDA for Imaging & Vision
- Segmentation
- Feature Processing
- Fast Scale Invariant Feature Detection and Matching on Programmable Graphics Hardware
- Fast Gain-Adaptive KLT Tracking on the GPU
- Stereo Imaging
- Machine Learning & Data Processing
- Large-scale Deep Unsupervised Learning using Graphics Processors
- Hardware Efficient Belief Propagation
- Fast k nearest neighbor search using GPU
- Biologically Inspired Computer Vision
Core Software Kernels for Imaging and Vision on CUDA GPUs
- Level-Set segmentation with CUDA
- Video segmentation with CUDA
- Multiclass SVM implementation in CUDA
- Pedestrian Detection
- SIFT (Scale Invariant Feature Transform)
- Optical Flow
- Libraries and collections
- GPU4Vision
- OpenVIDIA: Popular computer vision algorithms on CUDA including
- Stereo Vision
- Convolutions, Sobel, RMS, Histograms, Threshold, etc
- MinGPU: A minimum GPU library for Computer Vision
- NVPP: NVIDIA Performance Primitives (Early access: Focuses on image and video processing)