μNect: On Using a Gaming RGBD Camera in Micro-Metrology Applications

Abstract

Three-dimensional metrology problems are traditionally the domain of expensive devices like Laser-stripe sensors and custom-made projector-camera systems. The launch of Microsoft's Kinect sensor solved many of these problems which were deemed feasible only with several thousand-Dollar devices before. However, the sensor is highly tuned to its domain of application, which is the robust scanning of indoor environments at an accuracy range of few centimeters. In this work we investigate how the sensor can be modified to work at much higher accuracy, on a limited but scalable measurement range. By altering the sensor baseline and depth of field, we are able to reliably retrieve depth fields of objects at an accuracy in the sub-millimeter range. We further improve the sensor by adding multiple projectors, thus creating a low-cost multi-projector, single-camera system working at a frame rate of 30 Hz, at virtually no CPU consumption. We are hereby able to apply automated pattern intensity adaption and multi-view depth fusion in real-time and compete with a large range of sensors in terms of robustness, speed and accuracy, but at a fraction of the costs.