Feature Extraction and Modification for Illustrating 3D Stone Tools from Unorganized Point Clouds

Abstract

This paper presents a method for extracting and modifying features for illustrating stone tools. Features are detected from unorganized point clouds obtained by a 3D laser scanner. The curvature of each point in the point clouds is estimated by local surface fitting algorithm and used for detecting potential feature points. Feature lines are extracted by directionally growing algorithm. Our directionally feature line growing method is simple to detect feature lines from unorganized point data. The main idea of our method is to extract feature lines using principal curvatures and principal directions of the potential feature points along the axis directions and to merge all extracted lines. In the illustration of stone tools, to maintain form and manufacturing information, it requires to modify the detected features by specific knowledge on illustrating stone tools. Using the power of data parallel computation on the GPU, our method can be accelerated multiple times. Finally, our experimental results are compared to the actual illustrations drawn by archaeological illustrators.