Variational multi-valued velocity field estimation for transparent sequences.

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Standard

Variational multi-valued velocity field estimation for transparent sequences. / Ramírez-Manzanares, Alonso; Rivera, Mariano; Kornprobst, Pierre; Lauze, Francois Bernard.

I: Journal of Mathematical Imaging and Vision, Bind 40, Nr. 3, 2011, s. 285-304.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

Ramírez-Manzanares, A, Rivera, M, Kornprobst, P & Lauze, FB 2011, 'Variational multi-valued velocity field estimation for transparent sequences.', Journal of Mathematical Imaging and Vision, bind 40, nr. 3, s. 285-304. https://doi.org/10.1007/s10851-011-0260-8

APA

Ramírez-Manzanares, A., Rivera, M., Kornprobst, P., & Lauze, F. B. (2011). Variational multi-valued velocity field estimation for transparent sequences. Journal of Mathematical Imaging and Vision, 40(3), 285-304. https://doi.org/10.1007/s10851-011-0260-8

Vancouver

Ramírez-Manzanares A, Rivera M, Kornprobst P, Lauze FB. Variational multi-valued velocity field estimation for transparent sequences. Journal of Mathematical Imaging and Vision. 2011;40(3):285-304. https://doi.org/10.1007/s10851-011-0260-8

Author

Ramírez-Manzanares, Alonso ; Rivera, Mariano ; Kornprobst, Pierre ; Lauze, Francois Bernard. / Variational multi-valued velocity field estimation for transparent sequences. I: Journal of Mathematical Imaging and Vision. 2011 ; Bind 40, Nr. 3. s. 285-304.

Bibtex

@article{2077160c57fd42b48ec0dffa37d2bdaa,
title = "Variational multi-valued velocity field estimation for transparent sequences.",
abstract = "Motion estimation in sequences with transparenciesis an important problem in robotics and medicalimaging applications. In this work we propose avariational approach for estimating multi-valued velocityfields in transparent sequences. Starting from existinglocal motion estimators, we derive a variationalmodel for integrating in space and time such a localinformation in order to obtain a robust estimation ofthe multi-valued velocity field. With this approach, wecan indeed estimate multi-valued velocity fields whichare not necessarily piecewise constant on a layer –eachlayer can evolve according to a non-parametric opticalflow. We show how our approach outperforms existingmethods; and we illustrate its capabilities on challengingexperiments on both synthetic and real sequences.",
keywords = "Faculty of Science, transparent optical flow, Image regularization, Multiple motions, RDK sequences",
author = "Alonso Ram{\'i}rez-Manzanares and Mariano Rivera and Pierre Kornprobst and Lauze, {Francois Bernard}",
year = "2011",
doi = "10.1007/s10851-011-0260-8",
language = "English",
volume = "40",
pages = "285--304",
journal = "Journal of Mathematical Imaging and Vision",
issn = "0924-9907",
publisher = "Springer",
number = "3",

}

RIS

TY - JOUR

T1 - Variational multi-valued velocity field estimation for transparent sequences.

AU - Ramírez-Manzanares, Alonso

AU - Rivera, Mariano

AU - Kornprobst, Pierre

AU - Lauze, Francois Bernard

PY - 2011

Y1 - 2011

N2 - Motion estimation in sequences with transparenciesis an important problem in robotics and medicalimaging applications. In this work we propose avariational approach for estimating multi-valued velocityfields in transparent sequences. Starting from existinglocal motion estimators, we derive a variationalmodel for integrating in space and time such a localinformation in order to obtain a robust estimation ofthe multi-valued velocity field. With this approach, wecan indeed estimate multi-valued velocity fields whichare not necessarily piecewise constant on a layer –eachlayer can evolve according to a non-parametric opticalflow. We show how our approach outperforms existingmethods; and we illustrate its capabilities on challengingexperiments on both synthetic and real sequences.

AB - Motion estimation in sequences with transparenciesis an important problem in robotics and medicalimaging applications. In this work we propose avariational approach for estimating multi-valued velocityfields in transparent sequences. Starting from existinglocal motion estimators, we derive a variationalmodel for integrating in space and time such a localinformation in order to obtain a robust estimation ofthe multi-valued velocity field. With this approach, wecan indeed estimate multi-valued velocity fields whichare not necessarily piecewise constant on a layer –eachlayer can evolve according to a non-parametric opticalflow. We show how our approach outperforms existingmethods; and we illustrate its capabilities on challengingexperiments on both synthetic and real sequences.

KW - Faculty of Science

KW - transparent optical flow

KW - Image regularization

KW - Multiple motions

KW - RDK sequences

U2 - 10.1007/s10851-011-0260-8

DO - 10.1007/s10851-011-0260-8

M3 - Journal article

VL - 40

SP - 285

EP - 304

JO - Journal of Mathematical Imaging and Vision

JF - Journal of Mathematical Imaging and Vision

SN - 0924-9907

IS - 3

ER -

ID: 32338422