Abstract
In this work we present a new approach to study shape descriptors of archaeological objects using an implementation of the smoothed-points shape descriptor (SPSD) method that is based on the numerical mesh-free simulation method smoothed-particles hydrodynamics. SPSD can describe the textural or morphological properties of a surface by obtaining a property field descriptor based on the points shape descriptors and a smoothing function over a neighborhood of each point. The neighborhood size depends on a smoothing distance function which drives the field descriptor to either focus on small local details or larger details over big surfaces. SPSD is designed to provide a real-time scientific visualization of cloud points shape descriptors to assist in the field study of archaeological artifacts. It also has the potential to provide quantitative values (e.g. morphological properties) for artifacts analysis and classification (computational and archaeological). Due to the visualisation requirement for a real-time solution, SPSD is implemented in CUDA using an Octree method as the mechanism to solve the neighborhood particles interaction for each point cloud.
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Valdez, D.A.S. et al. (2020). CUDA Implementation of a Point Cloud Shape Descriptor Method for Archaeological Studies. In: Blanc-Talon, J., Delmas, P., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2020. Lecture Notes in Computer Science(), vol 12002. Springer, Cham. https://doi.org/10.1007/978-3-030-40605-9_39
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