Comparison of Kinect and Terrestrial LiDAR Capturing Natural Karst Cave 3-D Objects

Abstract

Modeling natural phenomena from 3-D information enhances our understanding of the environment. Dense 3-D point clouds are increasingly used as highly detailed input datasets. In addition to the capturing techniques of point clouds with LiDAR, low-cost sensors have been released in the last few years providing access to new research fields and facilitating 3-D data acquisition for a broader range of applications. This letter presents an analysis of different speleothem features using 3-D point clouds acquired with the gaming device Microsoft Kinect. We compare the Kinect sensor with terrestrial LiDAR reference measurements using the KinFu pipeline for capturing complete 3-D objects (<; 4 m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> ). The results demonstrate the suitability of the Kinect to capture flowstone walls and to derive morphometric parameters of cave features. Although the chosen capturing strategy (KinFu) reveals a high correlation (R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.92) of stalagmite morphometry along the vertical object axis, a systematic overestimation (22% for radii and 44% for volume) is found. The comparison of flowstone wall datasets predominantly shows low differences (mean of 1 mm with 7 mm standard deviation) of the order of the Kinect depth precision. For both objects the major differences occur at strongly varying and curved surface structures (e.g., with fine concave parts).