1Technical University of Munich 2Stanford University
We present a novel method to improve the robustness of real-time 3D surface reconstruction by incorporating inertial sensor data when determining inter-frame alignment. With commodity inertial sensors, we can significantly reduce the number of iterative closest point (ICP) iterations required per frame. Our system is also able to determine when ICP tracking becomes unreliable and use inertial navigation to correctly recover tracking, even after significant time has elapsed. This enables less experienced users to more quickly acquire 3D scans. We apply our framework to several different surface reconstruction tasks and demonstrate that enabling inertial navigation allows us to reconstruct scenes more quickly and recover from situations where reconstructing without IMU data produces very poor results.