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Artwork classification based on image features

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

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    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: 52
    Language of Content: Slovenian
    Mentor / Comentors:
    Name and SurnameIDFunction
    doc. dr. Luka Šajn307Mentor
    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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