This study uses computer vision models, which to some extent simulate the initial stages of human visual perception, to help categorize data in large sets of images of artworks by the artist Antoni Tàpies. The images have been analyzed on the basis of their compositional, chromatic and organizational characteristics, without textual notes, so that the analogies found may take us closer to, and help us to understand, the creator’s original values. The system as programmed can assist the specialist by establishing analogies between different artists or periods using the same criteria.

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©2019 ISAST
2019
ISAST

Supplementary data

SUPPLEMENTAL APPENDIX of the article “Computer Vision Models to Categorize Art Collections According to Visual Content: A New Approach to the Abstract Art of Antoni Tàpies” by Pilar Rosado

This text provides expanded details about computer vision models to categorize art collections according to visual content, specifically about the extraction of local descriptors, the Bag-of-Visual Terms (BOV) model, the K-means clustering algorithm and Information of the artworks by the artist Antoni Tàpies (Images © 2019, Pilar Rosado)

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