Abstract
To address the long-term statistical problem of ski-track area in the construction and operation of ski resorts, we propose a new ski-track point cloud boundary extraction method that improves the accuracy of boundary extraction and minimizes the offset of the area error. In this method, all point clouds are first projected onto the fitting plane using the random sample consensus (RANSAC) method. An improved point cloud boundary extraction algorithm is used to triangulate and extract the high-precision ski-track boundary. A discrete Green formula is then used to calculate and count the ski track’s exact area. It is demonstrated through five sets of test experiments that the error offset of the method proposed in this paper is smaller than that of other classical methods, which confirms its benefits and feasibility.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have