A Fast, Massively Parallel Solver for Large, Irregular Pairwise Markov Random Fields
Loading...
Date
2016
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Given the increasing availability of high-resolution input data, today's computer vision problems tend to grow beyond what has been considered tractable in the past. This is especially true for Markov Random Fields (MRFs), which have expanded beyond millions of variables with thousands of labels. Such MRFs pose new challenges for inference, requiring massively parallel solvers that can cope with large-scale problems and support general, irregular input graphs. We propose a block coordinate descent based solver for large MRFs designed to exploit many-core hardware such as recent GPUs. We identify tree-shaped subgraphs as a block coordinate scheme for irregular topologies and optimize them efficiently using dynamic programming. The resulting solver supports arbitrary MRF topologies efficiently and can handle arbitrary, dense or sparse label sets as well as label cost functions. Together with two additional heuristics for further acceleration, our solver performs favorably even compared to modern specialized solvers in terms of speed and solution quality, especially when solving very large MRFs.
Description
@inproceedings{10.2312:hpg.20161203,
booktitle = {Eurographics/ ACM SIGGRAPH Symposium on High Performance Graphics},
editor = {Ulf Assarsson and Warren Hunt},
title = {{A Fast, Massively Parallel Solver for Large, Irregular Pairwise Markov Random Fields}},
author = {Thuerck, Daniel and Waechter, Michael and Widmer, Sven and Buelow, Max von and Seemann, Patrick and Pfetsch, Marc E. and Goesele, Michael},
year = {2016},
publisher = {The Eurographics Association},
ISSN = {2079-8679},
ISBN = {978-3-03868-008-6},
DOI = {10.2312/hpg.20161203}
}