Robust 3D Surface Reconstruction in Real-Time with Localization Sensor

Abstract

SUMMARYWe present a system to improve the robustness of realtime 3D surface reconstruction by utilizing non-inertial localization sensor. Benefiting from such sensor, our easy-to-build system can effectively avoid tracking drift and lost comparing with conventional dense tracking and mapping systems. To best fusing the sensor, we first adopt a handeye calibration and performance analysis for our setup and then propose a novel optimization framework based on adaptive criterion function to improve the robustness as well as accuracy. We apply our system to several challenging reconstruction tasks, which show significant improvement in scanning robustness and reconstruction quality. key words: dense tracking and mapping, surface reconstruction, sensor fusion, RGB-D SLAM