Evaluating Photo Aesthetics Using Machine Learning

author: Domen Pogačnik, Faculty of Computer and Information Science, University of Ljubljana
published: Nov. 16, 2012,   recorded: October 2012,   views: 4252


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In this paper we propose a method for automatic assessment of aesthetic appeal of photographs. We identify signifi cant parameters that distinguish high quality photography from low quality snapshots. On the basis of these parameters, we de fined calculable features for automatic assessment of photography aesthetics using machine learning methods. The calculation of features depends heavily on the identifi cation of the subject in photographs. With the subject identi fied, we defi ned and implemented various features to analyze various aspects of a photograph. The features were tested on two datasets. First dataset was obtained from Flickr and manually labeled for evaluation. Second dataset was based on photographs from DPChallenge portal where subjects were identi ed with a face detection algorithm. Both experiments showed some promising results. In this article we specify the features which contribute to a successful classi cation of photographs, analyze their in influence and discuss the results. In conclusion, we off er some suggestions for further research.

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