Joint Unsupervised Deformable Spatio-Temporal Alignment of Sequences
File(s)zafeiriou2016joint.pdf (1.44 MB)
Accepted version
Author(s)
Zafeiriou, L
Antonakos, E
Zafeiriou, S
Pantic, M
Type
Conference Paper
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).
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).
Date Issued
2016-06-26
Date Acceptance
2016-03-02
Publisher
Computer Vision Foundation (CVF)
Copyright Statement
© the authors
Sponsor
Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (E
Grant Number
EP/J017787/1
EP/N007743/1
Source
International Conference on Computer Vision and Pattern Recognition
Publication Status
Accepted
Start Date
2016-06-26
Finish Date
2016-07-01
Coverage Spatial
Las Vegas, Nevada, USA