A Latent-Variable Lattice Model

Rajasekaran Masatran

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arXiv · 1512.07587

A Latent-Variable Lattice Model

Rajasekaran Masatran

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Abstract

Markov random field (MRF) learning is intractable, and its approximation algorithms are computationally expensive. We target a small subset of MRF that is used frequently in computer vision. We characterize this subset with three concepts: Lattice, Homogeneity, and Inertia; and design a non-markov model as an alternative. Our goal is robust learning from small datasets. Our learning algorithm uses vector quantization and, at time complexity O(U log U) for a dataset of U pixels, is much faster than that of general-purpose MRF.

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Rajasekaran Masatran. 2015-12-23. A Latent-Variable Lattice Model. https://arxiv.org/abs/1512.07587

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