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Paper details
Number 1 - March 2022
Volume 32 - 2022
A comprehensive study of clustering a class of 2D shapes
Agnieszka Kaliszewska, Monika Syga
Abstract
The paper is concerned with clustering with respect to the shape and size of 2D contours that are boundaries of cross-sections
of 3D objects of revolution. We propose a number of similarity measures based on combined disparate Procrustes
analysis (PA) and dynamic time warping (DTW) distances. A motivation and the main application for this study comes
from archaeology. The computational experiments performed refer to the clustering of archaeological pottery.
Keywords
shape representation, Procrustes distance, shape similarity, DTW, morphometrics, clustering, Kendall shape theory, typology of archaeological pottery