TY - GEN

T1 - The Influence of Color on Prices of Abstract Paintings

AU - Borisov, Maksim

AU - Kolycheva, Valeria

AU - Semenov, Alexander

AU - Grigoriev, Dmitry

N1 - Borisov, M., Kolycheva, V., Semenov, A., Grigoriev, D. (2023). The Influence of Color on Prices of Abstract Paintings. In: Dinh, T.N., Li, M. (eds) Computational Data and Social Networks . CSoNet 2022. Lecture Notes in Computer Science, vol 13831. Springer, Cham. https://doi.org/10.1007/978-3-031-26303-3_6

PY - 2023

Y1 - 2023

N2 - Determination of price of an artwork is a fundamental problem in cultural economics. In this work we investigate what impact visual characteristics of a painting have on its price. We construct a number of visual features in CIELAB color space measuring complexity of the painting, its points of interest using Discrete symmetry transform, segmentation-based features using Felzenszwalb segmentation and Regions adjacency graph merging, local color features from segmented image, features based on Itten and Kandinsky theories, and utilize mixed-effects model with authors bias as fixed effect to study impact of these features on the painting price. We analyze the influence of the color on the example of the most complex art style - abstractionism, created by Kandinsky, for which the color is the primary basis. We use Itten’s theory - the most recognized color theory in art history, from which the largest number of subtheories was born. For this day it is taken as the base for teaching artists. We utilize novel dataset of 3,885 paintings collected from Christie’s and Sotheby’s and find that color harmony has a little explanatory power, color complexity metrics are impact price negatively and color diversity explains price well.

AB - Determination of price of an artwork is a fundamental problem in cultural economics. In this work we investigate what impact visual characteristics of a painting have on its price. We construct a number of visual features in CIELAB color space measuring complexity of the painting, its points of interest using Discrete symmetry transform, segmentation-based features using Felzenszwalb segmentation and Regions adjacency graph merging, local color features from segmented image, features based on Itten and Kandinsky theories, and utilize mixed-effects model with authors bias as fixed effect to study impact of these features on the painting price. We analyze the influence of the color on the example of the most complex art style - abstractionism, created by Kandinsky, for which the color is the primary basis. We use Itten’s theory - the most recognized color theory in art history, from which the largest number of subtheories was born. For this day it is taken as the base for teaching artists. We utilize novel dataset of 3,885 paintings collected from Christie’s and Sotheby’s and find that color harmony has a little explanatory power, color complexity metrics are impact price negatively and color diversity explains price well.

UR - https://link.springer.com/chapter/10.1007/978-3-031-26303-3_6

U2 - 10.48550/arXiv.2206.04013

DO - 10.48550/arXiv.2206.04013

M3 - Conference contribution

SN - 9783031263026

T3 - Lecture Notes in Computer Science

SP - 64

EP - 68

BT - Computational Data and Social Networks

PB - Springer Nature

Y2 - 5 December 2022 through 7 December 2022

ER -