Efficient shape matching using vector extrapolation

Rodola E, Harada T, Kuniyoshi Y, Cremers D (2013)

Publication Type: Conference contribution

Publication year: 2013

Publisher: British Machine Vision Association, BMVA

Conference Proceedings Title: BMVC 2013 - Electronic Proceedings of the British Machine Vision Conference 2013

Event location: GBR

Abstract

We propose the adoption of a vector extrapolation technique to accelerate convergence of correspondence problems under the quadratic assignment formulation for attributed graph matching (QAP). In order to capture a broad range of matching scenarios, we provide a class of relaxations of the QAP under elastic net constraints. This allows us to regulate the sparsity/complexity trade-off which is inherent to most instances of the matching problem, thus enabling us to study the application of the acceleration method over a family of problems of varying difficulty. The validity of the approach is assessed by considering three different matching scenarios; namely, rigid and non-rigid three-dimensional shape matching, and image matching for Structure from Motion. As demonstrated on both real and synthetic data, our approach leads to an increase in performance of up to one order of magnitude when compared to the standard methods.

Involved external institutions

University of Tokyo

Japan (JP) Technische Universität München (TUM)

Germany (DE)

How to cite

APA:

Rodola, E., Harada, T., Kuniyoshi, Y., & Cremers, D. (2013). Efficient shape matching using vector extrapolation. In BMVC 2013 - Electronic Proceedings of the British Machine Vision Conference 2013. GBR: British Machine Vision Association, BMVA.

MLA:

Rodola, Emanuele, et al. "Efficient shape matching using vector extrapolation." Proceedings of the 2013 24th British Machine Vision Conference, BMVC 2013, GBR British Machine Vision Association, BMVA, 2013.

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