A comprehensive aesthetic quality assessment method for natural images using basic rules of photography

In this paper we propose a comprehensive photo aesthetic assessment method that represents each photo according to a set of photographic rules. Specifically, our method exploits the information derived from both low- and high-level analysis of photo layout, not only for the photo as a whole, but also for specific spatial regions of it. Five feature vectors are introduced for describing the photo's simplicity, colorfulness, sharpness, pattern and composition. Subsequently, they are concatenated in a final feature vector where a Support Vector Machine (SVM) classifier is applied in order to perform the aesthetic quality evaluation. The experimental results and comparisons show that our approach achieves consistently more accurate quality assessment than the relevant literature methods and also that the proposed features can be combined with other generic image features so as to enhance the performance of previous methods.

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