Evaluation of HoloLens Tracking and Depth Sensing for Indoor Mapping Applications The Microsoft HoloLens is a headworn mobile augmented reality device that is capable of mapping its direct environment in realtime as triangle meshes and localize itself within these threedimensional meshes simultaneously. The device is equipped with a variety of sensors including four tracking cameras and a timeofflight (ToF) range camera. Sensor images and their poses estimated by the builtin tracking system can be accessed by the user. This makes the HoloLens potentially interesting as an indoor mapping device. In this paper, we introduce the different sensors of the device and evaluate the complete system in respect of the task of mapping indoor environments. The overall quality of such a system depends mainly on the quality of the depth sensor together with its associated pose derived from the tracking system. For this purpose, we first evaluate the performance of the HoloLens depth sensor and its tracking system separately. Finally, we evaluate the overall system regarding its capability for mapping multiroom environments.

Hololens AR  Using VuforiaBased Marker Tracking Together with Text Recognition in an Assembly Scenario Many real world applications for Microsoft HoloLens*based applications suffer the problem of reliably recognizing and identifying movable objects within an environment. While the HoloLens is perfectly able to discern already known rooms, it still has troubles with reflecting surfaces or identically shaped objects. Using dedicated recognition libraries for each task poses the issue of shared resource access in the rather controlled HoloLens environmentIn this poster we present a solution for scenario with hard to track objects and similarly shaped objects for an electrical cabinet assembly task, where the reflective cabinet is tagged with a marker and the prefabricated cables are differentiated by textbased labels.