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Fast Non-Linear Methods for Dynamic Texture Prediction

Published on Oct 1, 2018 in ICIP (International Conference on Image Processing)
· DOI :10.1109/icip.2018.8451479
Sameeksha Katoch3
Estimated H-index: 3
(ASU: Arizona State University),
Pavan Turaga24
Estimated H-index: 24
(ASU: Arizona State University)
+ 1 AuthorsCihan Tepedelenlioglu26
Estimated H-index: 26
(ASU: Arizona State University)
Abstract
This paper aims to develop a fast dynamic-texture prediction method, using tools from non-linear dynamical modeling, and fast approaches for approximate regression. We consider dynamic textures to be described by patch-level non-linear processes, thus requiring tools such as delay-embedding to uncover a phase-space where dynamical evolution can be more easily modeled. After mapping the observed time-series from a dynamic texture video to its recovered phase-space, a time-efficient approximate prediction method is presented which utilizes locality-sensitive hashing approaches to predict possible phase-space vectors, given the current phase-space vector. Our experiments show the favorable performance of the proposed approach, both in terms of prediction fidelity, and computational time. The proposed algorithm is applied to shading prediction in utility scale solar arrays.
  • References (28)
  • Citations (2)
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7 CitationsSource
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10 CitationsSource
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Cited By2
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#2Sunil Rao (ASU: Arizona State University)H-Index: 4
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2 CitationsSource