QUANTIFYING SHAPE DESCRIPTORS FOR AESTHETIC CONCEPTS
DS 77: Proceedings of the DESIGN 2014 13th International Design Conference
Year: 2014
Editor: Marjanovic Dorian, Storga Mario, Pavkovic Neven, Bojcetic Nenad
Author: Zuniga, M.D.; Prieto, P.A.; Fantoni, G.
Series: DESIGN
Section: INDUSTRIAL DESIGN
Page(s): 2187-2194
Abstract
A new approach to quantitatively estimate the degree of perception of aesthetic concepts for object silhouettes is proposed. First, a survey has been conducted to obtain statistical measurements of the perception degree of the interviewees with respect to the opposite concept pair Gentle-Aggressive for a set of object silhouettes. Then, a new shape descriptor and the statistical measurement, associated to each silhouette, are utilized to train an artificial neural network. The obtained model allows predicting the perception degree of the studied aesthetic concepts for new silhouettes.
Keywords: object personality, shape descriptor, supervised learning