Premium
Statistics, vision, and the analysis of artistic style
Author(s) -
Graham Daniel J.,
Hughes James M.,
Leder Helmut,
Rockmore Daniel N.
Publication year - 2011
Publication title -
wiley interdisciplinary reviews: computational statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.693
H-Index - 38
eISSN - 1939-0068
pISSN - 1939-5108
DOI - 10.1002/wics.197
Subject(s) - exploratory data analysis , computer science , digitization , data science , statistical analysis , style (visual arts) , set (abstract data type) , artificial intelligence , statistical inference , pattern recognition (psychology) , statistics , data mining , computer vision , mathematics , art , visual arts , programming language
In the field of literature, there is an established set of techniques that have been successfully leveraged in the statistical analysis of literary style, most often to answer questions of authenticity and attribution. With the digitization of huge troves of art images come significant opportunities for the development of statistical techniques for the analysis of artistic style. In this article, we suggest that the progress made and statistical techniques developed in understanding visual processing as it relates to natural scenes can serve as a useful model and inspiration for visual stylometric analysis. WIREs Comput Stat 2012, 4:115–123. doi: 10.1002/wics.197 This article is categorized under: Statistical Learning and Exploratory Methods of the Data Sciences > Pattern Recognition Applications of Computational Statistics > Psychometrics Applications of Computational Statistics > Signal and Image Processing and Coding