Two step variational method for subpixel optical flow computation

Yoshihiko Mochizuki, Yusuke Kameda, Atsushi Imiya, Tomoya Sakai, Takashi Imaizumi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

We develop an algorithm for the super-resolution optical flow computation by combining variational super-resolution and the variational optical flow computation. Our method first computes the gradient and the spatial difference of a high resolution images from these of low resolution images directly, without computing any high resolution images. Second the algorithm computes optical flow of high resolution image using the results of the first step.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages1109-1118
Number of pages10
Volume5876 LNCS
EditionPART 2
DOIs
Publication statusPublished - 2009
Externally publishedYes
Event5th International Symposium on Advances in Visual Computing, ISVC 2009 - Las Vegas, NV
Duration: 2009 Nov 302009 Dec 2

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5876 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other5th International Symposium on Advances in Visual Computing, ISVC 2009
CityLas Vegas, NV
Period09/11/3009/12/2

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ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Mochizuki, Y., Kameda, Y., Imiya, A., Sakai, T., & Imaizumi, T. (2009). Two step variational method for subpixel optical flow computation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 2 ed., Vol. 5876 LNCS, pp. 1109-1118). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5876 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-10520-3_106