0000000000484248
AUTHOR
Gabriella Giordano
Linear density-based clustering with a discrete density model
Density-based clustering techniques are used in a wide range of data mining applications. One of their most attractive features con- sists in not making use of prior knowledge of the number of clusters that a dataset contains along with their shape. In this paper we propose a new algorithm named Linear DBSCAN (Lin-DBSCAN), a simple approach to clustering inspired by the density model introduced with the well known algorithm DBSCAN. Designed to minimize the computational cost of density based clustering on geospatial data, Lin-DBSCAN features a linear time complexity that makes it suitable for real-time applications on low-resource devices. Lin-DBSCAN uses a discrete version of the density m…
INTEGRATED SURVEYING AND MODELING TECHNIQUES FOR THE DOCUMENTATION AND VISUALIZATION OF THREE ANCIENT HOUSES IN THE MEDITERRANEAN AREA
The paper is focused on the layout and testing of a workflow for the documentation of archeological remains, addressed to the study, visualization and information data input. Topographic, laser scanning and photogrammetric data have been used to build up 3D textured models of three ancient houses built in Sicily and in Tunisia in the Hellenistic and Roman age. 3D models have been used to extract conventional representations (plans and sections), analyze the geometric and proportional features and propose a virtual reconstruction of the original layout. The final step of the research work has been addressed to the creation of a web-based tools for the visualization of the models addressed to…