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A Data-Driven Approach to Understanding Skill in Photographic Composition

  • Todd S. Sachs
  • Ramakrishna Kakarala
  • Shannon L. Castleman
  • Deepu Rajan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6469)

Abstract

Photography requires not only equipment but also skill to reliably produce aesthetically-pleasing results. It can be argued that, for photography, skill is apparent even without sophisticated equipment. However, no scientific tests have been carried out to confirm that supposition. For that matter, there has been little scientific study on whether skill is apparent, whether it can be discerned by judges in blind tests. We report results of an experiment in which 33 subjects were asked to use identical cameras to photograph each of 7 pre-determined scenes, including a portrait, landscapes, and several man-made objects. Each photograph was then rated in a double-blind manner by 8 judges. Of those judges, 3 are professional photographic experts, and 5 are imaging researchers. The results show that expert judges are able to discern photographic skill to a statistically significant level, but that the enthusiasts, who are more akin to the general public, are not. We also analyse the photos using computer vision methods published in the literature, and find that there is no correlation between human judgements and the previously-published machine learning methods.

Keywords

Skill Level Skill Rating Human Judge Photo Major Computer Vision Method 
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 2011

Authors and Affiliations

  • Todd S. Sachs
    • 1
  • Ramakrishna Kakarala
    • 2
  • Shannon L. Castleman
    • 2
  • Deepu Rajan
    • 2
  1. 1.Aptina ImagingSan JoseUSA
  2. 2.Nanyang Technological UniversitySingapore

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