OSCAR: On-site composition and aesthetics feedback through exemplars for photographers

Lei Yao, Poonam Suryanarayan, Mu Qiao, James Z. Wang, Jia Li

Research output: Contribution to journalArticlepeer-review

56 Scopus citations

Abstract

In this paper we describe a comprehensive system to enhance the aesthetic quality of the photographs captured by the mobile consumers. The system, named OSCAR, has been designed to provide on-site composition and aesthetics feedback through retrieved examples. We introduce three novel interactive feedback components. The first is the composition feedback which is qualitative in nature and responds by retrieving highly aesthetic exemplar images from the corpus which are similar in content and composition to the snapshot. The second is the color combination feedback which provides confidence on the snapshot to contain good color combinations. The third component is the overall aesthetics feedback which predicts the aesthetic ratings for both color and monochromatic images. An existing algorithm is used to provide ratings for color images, while new features and a new model are developed to treat monochromatic images. This system was designed keeping the next generation photography needs in mind and is the first of its kind. The feedback rendered is guiding and intuitive in nature. It is computed in situ while requiring minimal input from the user.

Original languageEnglish (US)
Pages (from-to)353-383
Number of pages31
JournalInternational Journal of Computer Vision
Volume96
Issue number3
DOIs
StatePublished - Feb 2012

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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