  We propose a novel method to tackle the visual-inertial localization problem
for constrained camera movements. We use residuals from the different
modalities to jointly optimize a global cost function. The residuals emerge
from IMU measurements, stereoscopic feature points, and constraints on possible
solutions in SE(3). In settings where dynamic disturbances are frequent, the
residuals reduce the complexity of the problem and make localization feasible.
We verify the advantages of our method in a suitable medical use case and
produce a dataset capturing a minimally invasive surgery in the abdomen. Our
novel clinical dataset MITI is comparable to state-of-the-art evaluation
datasets, contains calibration and synchronization and is available at
https://mediatum.ub.tum.de/1621941.
