Genre linked automated assessment and feedback of photographs based on visual aesthetics

This paper addresses the problem of automatically assessing the aesthetic quality of a photograph and providing actionable feedback to the photographer. Towards this task we have designed novel genre-specific attributes (for e.g. Noise level in a night mode photograph or Depth perception for the landscape mode). Using a collection of these mode relevant attributes we improved the assessment accuracy for three modes and reached state-of-the-art on the other one mode we investigated. These intuitive attributes are also visualized as a visual signature of the photograph. This representation can act as an actionable feedback to an aspiring amateur photographer.