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| Conference/Proceedings | IEEE International Conference on Multimedia and Expo |
| Start date | 10.07.2017 |
| End date | 14.07.2017 |
| Pages | 1183-1188 |
| Author(s) | Ruben Verhack, Thomas Sikora, Lieven Lange, Rolf Jongebloed, Glenn Van Wallendael, Peter Lambert |
| Title | [Best Student Paper] STEERED MIXTURE-OF-EXPERTS FOR LIGHT FIELD CODING, DEPTH ESTIMATION, AND PROCESSING |
| Abstract | The proposed framework, called Steered Mixture-of-Experts (SMoE), enables a multitude of processing tasks on light fields using a single unified Bayesian model. The underlying assumption is that light field rays are instantiations of a non-linear or non-stationary random process that can be modeled by piecewise stationary processes in the spatial domain. As such, it is modeled as a space-continuous Gaussian Mixture Model. Consequently, the model takes into account different regions of the scene, their edges, and their development along the spatial and disparity dimensions. Applications presented include light field coding, depth estimation, edge detection, segmentation, and view interpolation. The representation is compact, which allows for veryefficient compression yielding state-of-the-art coding resultsfor low bit-rates. Furthermore, due to the statistical representation, a vast amount of information can be queried from the model even without having to analyze the pixel values. This allows for “blind” light field processing and classification. |
| Key words | compression, light field coding, depth estimation, light field representations, mixture-of-experts, mixture models |
| Note | ISBN:978-1-5090-6067-2/17 |
| File | 1520Verhack2017.pdf |
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