Please use this identifier to cite or link to this item: doi:10.22028/D291-26282
Title: A multigrid platform for real-time motion computation with discontinuity-preserving variational methods
Author(s): Bruhn, Andrés
Weickert, Joachim
Kohlberger, Timo
Schnörr, Christoph
Language: English
Year of Publication: 2005
Free key words: computer vision
optic flow
differential techniques
DDC notations: 510 Mathematics
Publikation type: Other
Abstract: Variational methods are among the most accurate techniques for estimating the optic flow. They yield dense flow fields and can be designed such that they preserve discontinuities, allow to deal with large displacements and perform well under noise or varying illumination. However, such adaptations render the minimisation of the underlying energy functional very expensive in terms of computational costs: Typically, one or more large linear or nonlinear systems of equations have to be solved in order to obtain the desired solution. Consequently, variational methods are considered to be too slow for real-time performance. In our paper we address this problem in two ways: (i) We present a numerical framework based on bidirectional multigrid methods for accelerating a broad class of variational optic flow methods with different constancy and smoothness assumptions. In particular, discontinuity-preserving regularisation strategies are thereby in the focus of our work. (ii) We show by the examples of classical as well as more advanced variational techniques that real-time performance is possible - even for very complex optic flow models with high accuracy. Experiments show frame rates up to 63 dense flow fields per second for real-world image sequences of size 160 x 120 on a standard PC. Compared to classical iterative methods this constitutes a speedup of two to four orders of magnitude.
Link to this record: urn:nbn:de:bsz:291-scidok-45034
Series name: Preprint / Fachrichtung Mathematik, Universität des Saarlandes
Series volume: 136
Date of registration: 18-Jan-2012
Faculty: MI - Fakultät für Mathematik und Informatik
Department: MI - Mathematik
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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