Abstract
In this paper, I use the NVIDIA CUDA technology to perform the chroma key algorithm on stereoscopic images. NVIDIA CUDA allows to process parallel algorithms on GPU. Input data are stereoscopic images with the monochromatic background and the destination background image. Output data is the combination of inputs by using the chroma key. I compare the algorithm efficiency between the GPU and CPU execution.
Highlights
Processing stereoscopic imagesTo apply any graphic algorithm on the stereoscopic images we have to process both sub images
M1 Introduction U The chroma key algorithm provides the possibility of low cost virtual video studio creation
GPU is slower in the global memory access, which is the key operation in this algorithm
Summary
To apply any graphic algorithm on the stereoscopic images we have to process both sub images. The chroma key algorithm requires the same stereoscopic images format and images resolutions to process images as the standard 2-Dimension ones. If we have 2 incompatible input sources, we have to convert one to be compatible with the second one. Processing stereoscopic videos requires compatible frame standard and the same frame rate. If the inputs are not compatible we have to convert one to be compatible with the other one. The examplary stereoscopic chroma key processing block is shown
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