The Design of High-Level Features for Photo Quality Assessment

  • Authors:
  • Yan Ke;Xiaoou Tang;Feng Jing

  • Affiliations:
  • Microsoft Research Asia;Microsoft Research Asia;Microsoft Research Asia

  • Venue:
  • CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
  • Year:
  • 2006

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We propose a principled method for designing high level features forphoto quality assessment. Our resulting system can classify between high quality professional photos and low quality snapshots. Instead of using the bag of low-level features approach, we first determine the perceptual factors that distinguish between professional photos and snapshots. Then, we design high level semantic features to measure the perceptual differences. We test our features on a large and diverse dataset and our system is able to achieve a classification rate of 72% on this difficult task. Since our system is able to achieve a precision of over 90% in low recall scenarios, we show excellent results in a web image search application.