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PHOG-Derived Aesthetic Measures Applied to Color Photographs of Artworks, Natural Scenes and Objects
Christoph Redies2, Seyed Ali Amirshahi1, 2, Michael Koch1, 2, and Joachim Denzler1
1Computer Vision Group, Friedrich Schiller University Jena, Germany
seyed-ali.amirshahi@uni-jena.de
koch.michael@uni-jena.de
joachim.denzler@uni-jena.de
http://www.inf-cv.uni-jena.de
2Institute of Anatomy I, Friedrich Schiller University, Jena University Hospital, Germany
redies@mti.uni-jena.de
http://www.anatomie1.uniklinikum-jena.de
Abstract. Previous research in computational aesthetics has led to the identification of multiple image features that, in combination, can be related to the aesthetic quality of images, such as photographs. Moreover, it has been shown that aesthetic artworks possess specific higher-order statistical properties, such as a scale-invariant Fourier spectrum, that can be linked to coding mechanisms in the human visual system. In the present work, we derive novel measures based on a PHOG representation of images for image properties that have been studied in the context of the aesthetic assessment of images previously. We demonstrate that a large dataset of colored aesthetic paintings of Western provenance is characterized by a specific combination of the PHOG-derived aesthetic measures (high self-similarity, moderate complexity and low anisotropy). In this combination, the artworks differ significantly from seven other datasets of photographs that depict various types of natural and man-made scenes, patterns and objects. To the best of our knowledge, this is the first time that these features have been derived and evaluated on a large dataset of different image categories.
Keywords: Aesthetic, art, self-similarity, complexity, anisotropy, Birkhoff-like measure, Pyramid of Histograms of Orientation Gradients (PHOG)
LNCS 7583, p. 522 ff.
lncs@springer.com
© Springer-Verlag Berlin Heidelberg 2012