Proportion priors for image sequence segmentation
Nieuwenhuis C, Strekalovskiy E, Cremers D (2013)
Publication Type: Conference contribution
Publication year: 2013
Publisher: Institute of Electrical and Electronics Engineers Inc.
Pages Range: 2328-2335
Conference Proceedings Title: Proceedings of the IEEE International Conference on Computer Vision
Event location: AUS
ISBN: 9781479928392
Abstract
We propose a convex multilabel framework for image sequence segmentation which allows to impose proportion priors on object parts in order to preserve their size ratios across multiple images. The key idea is that for strongly deformable objects such as a gymnast the size ratio of respective regions (head versus torso, legs versus full body, etc.) is typically preserved. We propose different ways to impose such priors in a Bayesian framework for image segmentation. We show that near-optimal solutions can be computed using convex relaxation techniques. Extensive qualitative and quantitative evaluations demonstrate that the proportion priors allow for highly accurate segmentations, avoiding seeping-out of regions and preserving semantically relevant small-scale structures such as hands or feet. They naturally apply to multiple object instances such as players in sports scenes, and they can relate different objects instead of object parts, e.g. organs in medical imaging. The algorithm is efficient and easily parallelized leading to proportion-consistent segmentations at runtimes around one second. © 2013 IEEE.
Involved external institutions
University of California, Berkeley
United States (USA) (US)
Technische Universität München (TUM)
Germany (DE)
United States (USA) (US)
Technische Universität München (TUM)
Germany (DE)
How to cite
APA:
Nieuwenhuis, C., Strekalovskiy, E., & Cremers, D. (2013). Proportion priors for image sequence segmentation. In Proceedings of the IEEE International Conference on Computer Vision (pp. 2328-2335). AUS: Institute of Electrical and Electronics Engineers Inc..
MLA:
Nieuwenhuis, Claudia, Evgeny Strekalovskiy, and Daniel Cremers. "Proportion priors for image sequence segmentation." Proceedings of the 2013 14th IEEE International Conference on Computer Vision, ICCV 2013, AUS Institute of Electrical and Electronics Engineers Inc., 2013. 2328-2335.
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