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Studying Aesthetics in Photographic Images Using a Computational Approach

  • Ritendra Datta
  • Dhiraj Joshi
  • Jia Li
  • James Z. Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3953)

Abstract

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.

Keywords

Support Vector Machine Visual Feature Image Retrieval Photographic Image Aesthetic Quality 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ritendra Datta
    • 1
  • Dhiraj Joshi
    • 1
  • Jia Li
    • 1
  • James Z. Wang
    • 1
  1. 1.The Pennsylvania State UniversityUniversity ParkUSA

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