Artwork classification based on image features

Nejc Vesel (2015) Artwork classification based on image features. EngD thesis.

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Abstract

In this thesis we are trying to discover a method that allows us to attribute a painting to a particular artist with the help of image analysis. We are testing two methods. In the first one, we are trying to identify the style of a painter by analysing the way in which he translates a human face from a photograph into a painting. We are testing whether the differences on facial proportions in photographs and paintings are statistically significant. With the other method, we describe every painting with a set of features. The features look at the image color, texture and dimensions to form a feature vector. We test this on 10 pictures for each of the 3 painters with different styles. We are trying to test, whether we can correctly attribute these paintings to a painter just with these feature vectors.

Item Type:

Thesis (EngD thesis)

Keywords:

computer vision, art, face detection, artwork comparison, classification, artist classification

Number of Pages:

Language of Content:

Slovenian

Mentor / Comentors:

Name and Surname	ID	Function
doc. dr. Luka Šajn	307	Mentor

Link to COBISS:

http://www.cobiss.si/scripts/cobiss?command=search&base=51012&select=(ID=1536458179)

Institution:

University of Ljubljana

Department:

Faculty of Computer and Information Science

Item ID:

3033

Date Deposited:

02 Sep 2015 14:05

Last Modified:

14 Sep 2015 10:06

URI:

http://eprints.fri.uni-lj.si/id/eprint/3033

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