AI & Digitalization Breakfast Seminar: Certifiably Optimal Anisotropic Rotation Averaging

When: Wednesday October 15, 2025 at 09:00-10:00

Where: Control Seminar Room M:3170-73

Register: for free breakfast at the seminar, register no later than October 10th by using this link.

Abstract: Rotation averaging is a key subproblem in structure from motion. Semidefinite programming relaxations are often used to solve the problem, and there are theoretical results analyzing difficulty and optimality. However, previous methos focus on the isotropic setting, where the intrinsic uncertainties in the measurements are not fully incorporated into the resulting optimization task. Recent empirical results suggest that moving to an anisotropic framework, where these uncertainties are explicitly included, can result in an improvement of solution quality. However, global optimization for rotation averaging has remained a challenge in this scenario. In this talk we show how anisotropic costs can be incorporated in rotation averaging. We also demonstrate how existing solvers, designed for isotropic situations, fail in the anisotropic setting. Finally, we propose a stronger relaxation and empirically show that it recovers global optima on a number of tested datasets.

Speaker bio: Carl Olsson is a Professor at the Computer Vision and Machine Learning division at Centre for Mathematical Sciences, Lund University. He obtained his PhD at Lund University in 2009, and has since then been in Lund and at Chalmers. His research addresses large scale optimization methods with applications in computer vision. A particular interest is in mapping and navigation problems such as structure from motion. His research aims at improving reliability of algorithms by developing methods that provide globally optimal inference, independent of initialization.

The Breakfast Seminar Series is sponsored by the LTH Profile Area AI & Digitalization.