Exemplar-based image inpainting on the GPU applied to 3D video conversion




Wallace, Ryan

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My thesis investigates automation and optimizations for occlusion filling, a problem resulting from the generation of new viewpoints in the 3D video conversion process. Image inpainting is a popular topic in image processing research. The ability to fill a region of an image in a manner that is visually pleasing is a difficult and computationally expensive task. Recently, the most successful methods have been exemplar-based, copying patches of the image from a specified source region into the region to be filled. These algorithms are designed to propagate both structure and texture into the fill region. They are brute force algorithms however, and are generally implemented as sequential algorithms to be run on the CPU. In this research, I have effectively mapped the costly portions of an exemplar-based image inpainting algorithm to the GPU. I produce equivalent inpainting results in less time by parallelizing the brute force patch searching portion of the algorithm. Furthermore, I compare the results with another recent, optimized inpainting algorithm, and apply both algorithms to the real world problem of occlusion filling in a 3D video conversion pipeline.



Inpainting, 3D Conversion, GPU