Robust Group Synchronization via Quadratic Programming
This provides a robust solution for group synchronization tasks in fields like computer vision and robotics, though it appears incremental as it builds on existing frameworks.
The paper tackles the problem of robust group synchronization by proposing a quadratic programming formulation that estimates corruption levels, achieving tolerance up to the information-theoretic bound and exact recovery under mild conditions, as demonstrated in synthetic and real rotation averaging experiments.
We propose a novel quadratic programming formulation for estimating the corruption levels in group synchronization, and use these estimates to solve this problem. Our objective function exploits the cycle consistency of the group and we thus refer to our method as detection and estimation of structural consistency (DESC). This general framework can be extended to other algebraic and geometric structures. Our formulation has the following advantages: it can tolerate corruption as high as the information-theoretic bound, it does not require a good initialization for the estimates of group elements, it has a simple interpretation, and under some mild conditions the global minimum of our objective function exactly recovers the corruption levels. We demonstrate the competitive accuracy of our approach on both synthetic and real data experiments of rotation averaging.