Efficient Completion for Multi-Dimensional Real-World Data

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Multi-dimensional data such as 3D spatial data, image, video and so on is rapidly increasing. This research aims at developing a novel method of natural and completion instead of simple interpolation by analyzing multi-dimensional data and extracting characteristic values. Efficiency is one of the most important aspect to achieve natural completion because it is crucial to analyze huge multi-dimensional data. The project tried two approaches to this efficiency, namely, "efficient computation with SIMD processor" and "efficient computation by statistical algorithm". As for the former attempt, we focused on rendering of massive volume data and succeeded to accomplish the efficient implementation which allows GPU's full performance. As for the latter attempt, we experimented on facial-impression operation. We have succeeded to implement facial beautification method which preserves apparent age of the original face.