A Robust Translation Synchronization Algorithm

This paper introduces a robust translation synchronization approach which takes relative directions between pairs of images as inputs and outputs absolute image locations. Our approach is based on a generalized eigenvalue formulation, which contains edge weights in relative directions and vertex weights in absolute image translations. We present a rigorous stability analysis to determine how to set these weights optimally. Specifically, optimal vertex weights are always identical, whereas optimal edge weights depend on the magnitudes of relative translations and variances of relative directions. These results lead to an iterative synchronization procedure, which progressively removes outliers in the inputs by adaptively adjusting the edge weights. Experimental results justify our theoretical results and show that our approach outperforms state-of-the-art baseline approaches on both synthetic and real datasets.