視覺呈像

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.

Technical Reports on using CUDA for Imaging & Vision

Segmentation

"CUDA cuts: Fast graph cuts on the GPU"

Feature Processing

Stereo Imaging

Stereo depth with a Unified Architecture GPU

Machine Learning & Data Processing

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)