3D indoor modeling with low-cost RGB-D camera and iPad Pro: A Comparative Study
Keywords: RGB-D sensor, iPad Pro LiDAR, Kinect Azure, Indoor 3D reconstruction, 3D modeling
Abstract. The rapid advancement in indoor 3D building modeling has led to increased interest in low-cost solutions for 3D data acquisition. While Terrestrial Laser Scanning (TLS) and Mobile Mapping Systems (MMS) produce detailed 3D models, their high cost and complex workflows make them impractical for many applications. In this paper, we investigate the effectiveness of using low-cost sensors, specifically RGB-D camera and iPad Pro for 3D modelling. Through a series of experiments, we evaluate these devices in terms of data accuracy, processing speed, and qualitative analysis using 3D point clouds and heat map visualizations, comparing the results with MMS data as the ground truth. Three distinct environments: an office room, a corridor, and a staircase were scanned to assess performance across varying levels of scene complexity. The results show that both devices are effective for indoor 3D modeling, but the RGB-D camera was more accurate, with an average C2C distance of 0.0245 meters compared to the iPad’s 0.0465 meters. However, the iPad Pro was faster, completing scans 30% quicker, making it better suited for tasks that require speed over precision.