Classification of optical flow by constraints

Yusuke Kameda, Atsushi Imiya

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

3 Citations (Scopus)

Abstract

In this paper, we analyse mathematical properties of spatial optical-flow computation algorithm. First by numerical analysis, we derive the convergence property on variational optical-flow computation method used for cardiac motion detection. From the convergence property of the algorithm, we clarify the condition for the scheduling of the regularisation parameters. This condition shows that for the accurate and stable computation with scheduling the regularisation coefficients, we are required to control the sampling interval for numerical computation.

Original languageEnglish
Title of host publicationComputer Analysis of Images and Patterns - 12th International Conference, CAIP 2007, Proceedings
PublisherSpringer Verlag
Pages61-68
Number of pages8
ISBN (Print)9783540742715
DOIs
Publication statusPublished - 1 Jan 2007
Event12th International Conference on Computer Analysis of Images and Patterns, CAIP 2007 - Vienna, Austria
Duration: 27 Aug 200729 Aug 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4673 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th International Conference on Computer Analysis of Images and Patterns, CAIP 2007
CountryAustria
CityVienna
Period27/08/0729/08/07

Cite this

Kameda, Y., & Imiya, A. (2007). Classification of optical flow by constraints. In Computer Analysis of Images and Patterns - 12th International Conference, CAIP 2007, Proceedings (pp. 61-68). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4673 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-540-74272-2_8