---
_id: '3198'
abstract:
- lang: eng
text: 'In this paper we present a new approach for establishing correspondences
between sparse image features related by an unknown non-rigid mapping and corrupted
by clutter and occlusion, such as points extracted from a pair of images containing
a human figure in distinct poses. We formulate this matching task as an energy
minimization problem by defining a complex objective function of the appearance
and the spatial arrangement of the features. Optimization of this energy is an
instance of graph matching, which is in general a NP-hard problem. We describe
a novel graph matching optimization technique, which we refer to as dual decomposition
(DD), and demonstrate on a variety of examples that this method outperforms existing
graph matching algorithms. In the majority of our examples DD is able to find
the global minimum within a minute. The ability to globally optimize the objective
allows us to accurately learn the parameters of our matching model from training
examples. We show on several matching tasks that our learned model yields results
superior to those of state-of-the-art methods. '
alternative_title:
- LNCS
author:
- first_name: Lorenzo
full_name: Torresani, Lorenzo
last_name: Torresani
- first_name: Vladimir
full_name: Vladimir Kolmogorov
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
- first_name: Carsten
full_name: Rother, Carsten
last_name: Rother
citation:
ama: 'Torresani L, Kolmogorov V, Rother C. Feature correspondence via graph matching:
Models and global optimization. In: Vol 5303. Springer; 2008:596-609. doi:10.1007/978-3-540-88688-4_44'
apa: 'Torresani, L., Kolmogorov, V., & Rother, C. (2008). Feature correspondence
via graph matching: Models and global optimization (Vol. 5303, pp. 596–609). Presented
at the ECCV: European Conference on Computer Vision, Springer. https://doi.org/10.1007/978-3-540-88688-4_44'
chicago: 'Torresani, Lorenzo, Vladimir Kolmogorov, and Carsten Rother. “Feature
Correspondence via Graph Matching: Models and Global Optimization,” 5303:596–609.
Springer, 2008. https://doi.org/10.1007/978-3-540-88688-4_44.'
ieee: 'L. Torresani, V. Kolmogorov, and C. Rother, “Feature correspondence via graph
matching: Models and global optimization,” presented at the ECCV: European Conference
on Computer Vision, 2008, vol. 5303, pp. 596–609.'
ista: 'Torresani L, Kolmogorov V, Rother C. 2008. Feature correspondence via graph
matching: Models and global optimization. ECCV: European Conference on Computer
Vision, LNCS, vol. 5303, 596–609.'
mla: 'Torresani, Lorenzo, et al. Feature Correspondence via Graph Matching: Models
and Global Optimization. Vol. 5303, Springer, 2008, pp. 596–609, doi:10.1007/978-3-540-88688-4_44.'
short: L. Torresani, V. Kolmogorov, C. Rother, in:, Springer, 2008, pp. 596–609.
conference:
name: 'ECCV: European Conference on Computer Vision'
date_created: 2018-12-11T12:01:58Z
date_published: 2008-01-01T00:00:00Z
date_updated: 2021-01-12T07:41:44Z
day: '01'
doi: 10.1007/978-3-540-88688-4_44
extern: 1
intvolume: ' 5303'
main_file_link:
- open_access: '0'
url: http://research-srv.microsoft.com/pubs/70610/eccv08-MatchingMRF.pdf
month: '01'
page: 596 - 609
publication_status: published
publisher: Springer
publist_id: '3485'
quality_controlled: 0
status: public
title: 'Feature correspondence via graph matching: Models and global optimization'
type: conference
volume: 5303
year: '2008'
...