The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLVIII-1/W1-2023
https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-167-2023
https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-167-2023
25 May 2023
 | 25 May 2023

COMBINING HOLOLENS WITH INSTANT-NERFS: ADVANCED REAL-TIME 3D MOBILE MAPPING

D. Haitz, B. Jutzi, M. Ulrich, M. Jäger, and P. Hübner

Keywords: Neural Radiance Fields, Fast 3D Reconstruction, Real-Time, HoloLens, Machine Vision, Mobile Mapping

Abstract. This work represents a large step into modern ways of fast 3D reconstruction based on RGB camera images. Utilizing a Microsoft HoloLens 2 as a multisensor platform that includes an RGB camera and an inertial measurement unit for SLAM-based camera-pose determination, we train a Neural Radiance Field (NeRF) as a neural scene representation in real-time with the acquired data from the HoloLens. The HoloLens is connected via Wifi to a high-performance PC that is responsible for the training and 3D reconstruction. After the data stream ends, the training is stopped and the 3D reconstruction is initiated, which extracts a point cloud of the scene. With our specialized inference algorithm, five million scene points can be extracted within 1 second. In addition, the point cloud also includes radiometry per point. Our method of 3D reconstruction outperforms grid point sampling with NeRFs by multiple orders of magnitude and can be regarded as a complete real-time 3D reconstruction method in a mobile mapping setup.