2008 · 96 citations · 26 references
ComputingComputer ScienceHigh-performance ComputingComputer GraphicsComputer VisionParallel ComputingComputer Graphics HardwareGraphics Processing Unit ArchitectureGraphics Processing Unit ComputingGraphics Processing UnitsHardware AccelerationImage ProcessingCompute Unified Device ArchitectureComputer Vision AccelerationCuda ProgrammingGpu AcceleratorsGpu Parallel AlgorithmsGpu Programming ModelsImage Processing On GpusImage Processing Units
Graphics and vision are approximate inverses of each other: ordinarily graphics processing units (GPUs) are used to convert ldquonumbers into picturesrdquo (i.e. computer graphics). In this paper, we discuss the use of GPUs in approximately the reverse way: to assist in ldquoconverting pictures into numbersrdquo (i.e. computer vision). For graphical operations, GPUs currently provide many hundreds of gigaflops of processing power. This paper discusses how this processing power is being harnessed for image processing and computer vision, thereby providing dramatic speedups on commodity, readily available graphics hardware. A brief review of algorithms mapped to the GPU by using the graphics API for vision is presented. The NVIDIA CUDA programming model is then introduced as a way of expressing program parallelism without the need for graphics expertise.
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A Survey of General‐Purpose Computation on Graphics Hardware
John D. Owens, David Luebke, Naga K. Govindaraju et al. · Computer Graphics Forum · 2007 · 2K citations
GPU Cluster for High Performance Computing
Zhe Fan, Feng Qiu, Arie Kaufman et al. · 2005 · 438 citations
Multi-resolution real-time stereo on commodity graphics hardware
Ruigang Yang, Marc Pollefeys · 2003 · 273 citations
James Fung, Steve Mann · 2005 · 202 citations