Point-based Simplification Algorithm

This study presents a novel, rapid, and effective point simplification algorithm based on a point cloud without any normal and connectivity information. This study is initiated with a scattered sampled point set in three dimensions, and the final output is a triangular mesh model, which is simplified according to a restrictive criteria. The proposed method reduces the number of calculations required to establish the relation between triangulation and the connectivity. Due to the continuous development of computer graphics technology, diversified virtual reality applications are being increasingly adopted. Recently, the efficient and vivid portrayal of 3D objects in the real world in virtual scenes has become a crucial issue in computer graphics. A triangular mesh is one of the most popular data structures for representing 3D models in applications. Numerous methods currently exist for constructing objects using surface reconstruction. The data required for the sampled points are generally obtained from a laser scanner. However, the extracted sampled points are frequently affected by shape variation. The number of triangles created increases with the number of points sampled from the surface of a 3D object, which helps in the reconstruction of the correct model. Nevertheless, subsequent graphics applications, such as morphing or rendering, increase the computation costs. Appropriate relevant points should be chosen so as to retain the object features and reduce the storage space and calculation costs. Key-Words: point simplification, discrete shape operator, feature extraction, curvature, torsion.