Abstract
Motion estimation in sequences with transparencies
is an important problem in robotics and medical
imaging applications. In this work we propose a
variational approach for estimating multi-valued velocity
fields in transparent sequences. Starting from existing
local motion estimators, we derive a variational
model for integrating in space and time such a local
information in order to obtain a robust estimation of
the multi-valued velocity field. With this approach, we
can indeed estimate multi-valued velocity fields which
are not necessarily piecewise constant on a layer –each
layer can evolve according to a non-parametric optical
flow. We show how our approach outperforms existing
methods; and we illustrate its capabilities on challenging
experiments on both synthetic and real sequences.
is an important problem in robotics and medical
imaging applications. In this work we propose a
variational approach for estimating multi-valued velocity
fields in transparent sequences. Starting from existing
local motion estimators, we derive a variational
model for integrating in space and time such a local
information in order to obtain a robust estimation of
the multi-valued velocity field. With this approach, we
can indeed estimate multi-valued velocity fields which
are not necessarily piecewise constant on a layer –each
layer can evolve according to a non-parametric optical
flow. We show how our approach outperforms existing
methods; and we illustrate its capabilities on challenging
experiments on both synthetic and real sequences.
| Originalsprog | Engelsk |
|---|---|
| Tidsskrift | Journal of Mathematical Imaging and Vision |
| Vol/bind | 40 |
| Udgave nummer | 3 |
| Sider (fra-til) | 285-304 |
| Antal sider | 20 |
| ISSN | 0924-9907 |
| DOI | |
| Status | Udgivet - jul. 2011 |
Emneord
- Det Natur- og Biovidenskabelige Fakultet