Indoor 3D Reconstruction of Buildings via Azure Kinect RGB-D Camera

With the development of 3D vision techniques, RGB-D cameras are increasingly used to allow easier and cheaper access to the third dimension. In this paper, we focus on testing the potential of the Kinect Azure RGB-D camera in the 3D reconstruction of indoor scenes. First, a series of investigations of the hardware was performed to evaluate its accuracy and precision. The results show that the measurements made with the Azure could be exploited for close-range survey applications. Second, we performed a methodological workflow for indoor reconstruction based on the Open3D framework, which was applied to two different indoor scenes. Based on the results, we can state that the quality of 3D reconstruction significantly depends on the architecture of the captured scene. This was supported by a comparison of the point cloud from the Kinect Azure with that from a terrestrial laser scanner and another from a mobile laser scanner. The results show that the average differences do not exceed 8 mm, which confirms that the Kinect Azure can be considered a 3D measurement system at least as reliable as a mobile laser scanner.