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27132 Joint Unsupervised Deformable Spatio-Temporal Alignment of Sequences
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Zafeiriou, L. and Antonakos, E. and Zafeiriou, S. and Pantic, M. (2016) Joint Unsupervised Deformable Spatio-Temporal Alignment of Sequences. In: Proceedings of IEEE International Conference on Computer Vision & Pattern Recognition (CVPR 2016), 26 June - 1 July 2016, Las Vegas, USA. pp. 3382-3390. IEEE Computer Vision and Pattern Recognition. ISSN 1063-6919 ISBN 978-1-4673-8852-8

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Official URL: http://dx.doi.org/10.1109/CVPR.2016.368

Abstract

Typically, the problems of spatial and temporal alignment
of sequences are considered disjoint. That is, in order
to align two sequences, a methodology that (non)-rigidly
aligns the images is first applied, followed by temporal
alignment of the obtained aligned images. In this paper, we
propose the first, to the best of our knowledge, methodology
that can jointly spatio-temporally align two sequences,
which display highly deformable texture-varying objects.
We show that by treating the problems of deformable spatial
and temporal alignment jointly, we achieve better results
than considering the problems independent. Furthermore,
we show that deformable spatio-temporal alignment
of faces can be performed in an unsupervised manner (i.e.,
without employing face trackers or building person-specific
deformable models).

Item Type:Conference or Workshop Paper (Full Paper, Talk)
Research Group:EWI-HMI: Human Media Interaction
Research Program:CTIT-General
Research Project:FROG: Fun Robotic Outdoor Guide, TERESA: Telepresence Reinforcement-learning Social Agent
Uncontrolled Keywords:deformable spatial and temporal alignment of sequences,
ID Code:27132
Status:Published
Deposited On:20 April 2017
Refereed:Yes
International:Yes
More Information:statistics

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