Optimal transport for vector Gaussian mixture models
This work addresses the problem of efficiently applying optimal mass transport to vector-valued data, potentially benefiting fields like color imagery analysis.
This paper explores the application of optimal mass transport (OMT) to vector-valued Gaussian mixture models (VGMMs). The authors claim that using VGMMs for OMT offers benefits in computational efficiency and structure preservation.
Vector-valued Gaussian mixtures form an important special subset of vector-valued distributions. In general, vector-valued distributions constitute natural representations for physical entities, which can mutate or transit among alternative manifestations distributed in a given space. A key example is color imagery. In this note, we vectorize the Gaussian mixture model and study several different optimal mass transport related problems associated to such models. The benefits of using vector Gaussian mixture for optimal mass transport include computational efficiency and the ability to preserve structure.