@online{Bernard_arXIv1811.10541,
TITLE = {Higher-order Projected Power Iterations for Scalable Multi-Matching},
AUTHOR = {Bernard, Florian and Thunberg, Johan and Swoboda, Paul and Theobalt, Christian},
LANGUAGE = {eng},
URL = {http://arxiv.org/abs/1811.10541},
EPRINT = {1811.10541},
EPRINTTYPE = {arXiv},
YEAR = {2018},
ABSTRACT = {The matching of multiple objects (e.g. shapes or images) is a fundamental<br>problem in vision and graphics. In order to robustly handle ambiguities, noise<br>and repetitive patterns in challenging real-world settings, it is essential to<br>take geometric consistency between points into account. Computationally, the<br>multi-matching problem is difficult. It can be phrased as simultaneously<br>solving multiple (NP-hard) quadratic assignment problems (QAPs) that are<br>coupled via cycle-consistency constraints. The main limitations of existing<br>multi-matching methods are that they either ignore geometric consistency and<br>thus have limited robustness, or they are restricted to small-scale problems<br>due to their (relatively) high computational cost. We address these<br>shortcomings by introducing a Higher-order Projected Power Iteration method,<br>which is (i) efficient and scales to tens of thousands of points, (ii)<br>straightforward to implement, (iii) able to incorporate geometric consistency,<br>and (iv) guarantees cycle-consistent multi-matchings. Experimentally we show<br>that our approach is superior to existing methods.<br>},
}