@inproceedings{2f9fa70a34d6461cb592ba715da9d186,
title = "Surface area estimation using 3D point clouds and Delaunay triangulation",
abstract = "Estimating the surface area of a stockpile is a crucial challenge in several fields, including in construction projects. While modern remote sensing platforms are increasingly popular, their utility in indoor stockpiles is limited, and their use in outdoor settings can be cost-prohibitive. This study presents a straightforward and cost-effective approach for estimating the surface area of both indoor and outdoor stockpiles using 3D point cloud data and the Delaunay triangulation technique. A mobile phone camera is used to capture a video of the stockpile, from which a 3D point cloud is generated, followed by the production of a mesh to reconstruct its surface via Delaunay triangulation. The proposed method{\textquoteright}s output is the stockpile{\textquoteright}s surface area, which is estimated by summing the surfaces of individual triangles. Experimental results from a laboratory setting on small-scale stockpiles indicate that this method is an effective approach to measuring stockpile surface areas and has the potential for widespread use in various stockpiles in different settings.",
keywords = "3D Point Cloud, Delaunay Trian-gulation, Image and Video Processing, Smart 3D Model Reconstruction, Surface Area Estimation",
author = "Helia Farhood and Samuel Muller and Amin Beheshti",
year = "2023",
doi = "10.1007/978-3-031-35308-6\_3",
language = "English",
isbn = "9783031353079",
series = "Lecture Notes in Networks and Systems",
publisher = "Springer, Springer Nature",
pages = "28--39",
editor = "Kevin Daimi and \{Al Sadoon\}, Abeer",
booktitle = "Proceedings of the Second International Conference on Innovations in Computing Research (ICR{\textquoteright}23)",
address = "United States",
note = "2nd International Conference on Innovations in Computing Research, ICR 2023 ; Conference date: 04-09-2023 Through 06-09-2023",
}