Conference item
Filter-based mean-field inference for random fields with higher-order terms and product label-spaces
- Abstract:
- Recently, a number of cross bilateral filtering methods have been proposed for solving multi-label problems in computer vision, such as stereo, optical flow and object class segmentation that show an order of magnitude improvement in speed over previous methods. These methods have achieved good results despite using models with only unary and/or pairwise terms. However, previous work has shown the value of using models with higher-order terms e.g. to represent label consistency over large regions, or global co-occurrence relations. We show how these higher-order terms can be formulated such that filter-based inference remains possible. We demonstrate our techniques on joint stereo and object labeling problems, as well as object class segmentation, showing in addition for joint object-stereo labeling how our method provides an efficient approach to inference in product label-spaces. We show that we are able to speed up inference in these models around 10-30 times with respect to competing graph-cut/move-making methods, as well as maintaining or improving accuracy in all cases. We show results on PascalVOC-10 for object class segmentation, and Leuven for joint object-stereo labeling.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 1.7MB, Terms of use)
-
- Publisher copy:
- 10.1007/978-3-642-33715-4_3
Authors
+ Engineering and Physical Sciences Research Council
More from this funder
- Funder identifier:
- https://ror.org/0439y7842
- Publisher:
- Springer
- Host title:
- Computer Vision – ECCV 2012: 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012. Proceedings, Part V
- Pages:
- 31-44
- Series:
- Lecture Notes in Computer Science
- Series number:
- 7576
- Place of publication:
- Berlin, Heidelberg
- Publication date:
- 2012-09-26
- Acceptance date:
- 2024-06-25
- Event title:
- 12th European Conference on Computer Vision (ECCV 2012)
- Event location:
- Florence, Italy
- Event website:
- https://eccv2012.unifi.it/
- Event start date:
- 2012-10-07
- Event end date:
- 2012-10-13
- DOI:
- EISSN:
-
1611-3349
- ISSN:
-
0302-9743
- EISBN:
- 9783642337154
- ISBN:
- 9783642337147
- Language:
-
English
- Pubs id:
-
971485
- Local pid:
-
pubs:971485
- Deposit date:
-
2024-05-17
Terms of use
- Copyright holder:
- Springer-Verlag Berlin Heidelberg
- Copyright date:
- 2012
- Rights statement:
- © 2012 Springer-Verlag Berlin Heidelberg.
- Notes:
- This is the accepted manuscript version of the paper. The final version is available online from Springer at https://dx.doi.org/10.1007/978-3-642-33715-4_3
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