  We propose a new benchmark for evaluating stereoscopic visual-inertial
computer vision algorithms (SLAM/ SfM/ 3D Reconstruction/ Visual-Inertial
Odometry) for minimally invasive surgical (MIS) interventions in the abdomen.
Our MITI Dataset available at [https://mediatum.ub.tum.de/1621941] provides all
the necessary data by a complete recording of a handheld surgical intervention
at Research Hospital Rechts der Isar of TUM. It contains multimodal sensor
information from IMU, stereoscopic video, and infrared (IR) tracking as ground
truth for evaluation. Furthermore, calibration for the stereoscope,
accelerometer, magnetometer, the rigid transformations in the sensor setup, and
time-offsets are available. We wisely chose a suitable intervention that
contains very few cutting and tissue deformation and shows a full scan of the
abdomen with a handheld camera such that it is ideal for testing SLAM
algorithms. Intending to promote the progress of visual-inertial algorithms
designed for MIS application, we hope that our clinical training dataset helps
and enables researchers to enhance algorithms.
