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Fast MRF Optimization with Application to Depth Reconstruction

2019-12-11 | |  96 |   47 |   0

Abstract

We describe a simple and fast algorithm for optimizing Markov random fifields over images. The algorithm performs block coordinate descent by optimally updating a horizontal or vertical line in each step. While the algorithm is not as accurate as state-of-the-art MRF solvers on traditional benchmark problems, it is trivially parallelizable and produces competitive results in a fraction of a second. As an application, we develop an approach to increasing the accuracy of consumer depth cameras. The presented algorithm enables high-resolution MRF optimization at multiple frames per second and substantially increases the accuracy of the produced range images.

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