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.

Original languageEnglish (US)
Title of host publication2018 IEEE International Conference on Image Processing, ICIP 2018 - Proceedings
PublisherIEEE Computer Society
Pages2107-2111
Number of pages5
ISBN (Electronic)9781479970612
DOIs
StatePublished - Aug 29 2018
Event25th IEEE International Conference on Image Processing, ICIP 2018 - Athens, Greece
Duration: Oct 7 2018Oct 10 2018

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Conference

Conference25th IEEE International Conference on Image Processing, ICIP 2018
CountryGreece
CityAthens
Period10/7/1810/10/18

Keywords

  • Dynamic textures
  • Phase-space reconstruction
  • Shading prediction
  • Solar energy

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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  • Cite this

    Katoch, S., Turaga, P., Spanias, A., & Tepedelenlioglu, C. (2018). Fast Non-Linear Methods for Dynamic Texture Prediction. In 2018 IEEE International Conference on Image Processing, ICIP 2018 - Proceedings (pp. 2107-2111). [8451479] (Proceedings - International Conference on Image Processing, ICIP). IEEE Computer Society. https://doi.org/10.1109/ICIP.2018.8451479