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Towards Computational Models of the Visual Aesthetic Appeal of Consumer Videos

  • Anush K. Moorthy
  • Pere Obrador
  • Nuria Oliver
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6315)

Abstract

In this paper, we tackle the problem of characterizing the aesthetic appeal of consumer videos and automatically classifying them into high or low aesthetic appeal. First, we conduct a controlled user study to collect ratings on the aesthetic value of 160 consumer videos. Next, we propose and evaluate a set of low level features that are combined in a hierarchical way in order to model the aesthetic appeal of consumer videos. After selecting the 7 most discriminative features, we successfully classify aesthetically appealing vs. aesthetically unappealing videos with a 73% classification accuracy using a support vector machine.

Keywords

Support Vector Machine Ground Truth Motion Vector Mean Opinion Score Image Quality Assessment 
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 2010

Authors and Affiliations

  • Anush K. Moorthy
    • 1
  • Pere Obrador
    • 1
  • Nuria Oliver
    • 1
  1. 1.Telefonica ResearchBarcelonaSpain

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