Studying Aesthetics in Photographic Images
Using a Computational Approach
Ritendra Datta, Dhiraj Joshi, Jia Li, James Z. Wang
The Pennsylvania State University
Aesthetics, in the world of art and photography, refers to
the principles of the nature and appreciation of beauty. Judging beauty
and other aesthetic qualities of photographs is a highly subjective task.
Hence, there is no unanimously agreed standard for measuring aesthetic
value. In spite of the lack of firm rules, certain features in photographic
images are believed, by many, to please humans more than certain
others. In this paper, we treat the challenge of automatically inferring
aesthetic quality of pictures using their visual content as a machine
learning problem, with a peer-rated online photo sharing Website as
data source. We extract certain visual features based on the intuition
that they can discriminate between aesthetically pleasing and displeasing
images. Automated classifiers are built using support vector machines
and classification trees. Linear regression on polynomial terms of the
features is also applied to infer numerical aesthetics ratings. The work
attempts to explore the relationship between emotions which pictures
arouse in people, and their low-level content. Potential applications
include content-based image retrieval and digital photography.
Full color PDF file
Ritendra Datta, Dhiraj Joshi, Jia Li and James Z. Wang, ``Studying
Aesthetics in Photographic Images Using a Computational Approach,''
Lecture Notes in Computer Science, vol. 3953, Proceedings of the
European Conference on Computer Vision, Part III, pp. 288-301, Graz,
Austria, May 2006.
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February 17, 2006.
© 2006, James Z. Wang