Dataset for the Aesthetic Value Automatic Prediction

Abstract

One of the most relevant issue in the prediction and classification of the aesthetic value of an image is the sample set used to train and validate the computational system. In this document the limitations found in different datasets used to classificate and predict aesthetic values are exposed, and a new dataset is proposed with images from the DPChallenge.com portal, with evaluations of three different populations.

Digital Image Quality Prediction System

“…After analyzing the degree of generalization of some datasets used in automatic image prediction, it was concluded that it was not enough to consider them as a reference in the training of automatic image prediction and classification systems. Taking this into account, a new set of images from the web portal DPChallenge.com was developed in search of greater statistical consistency [7].…”

“…In this case, unlike other image quality assessment algorithms that use synthetically distorted images [3,4], it was decided to use images with absence of distortion [5,6]. Despite the fact that the data collected contained quality and aesthetic results, on this occasion only the quality data were used as they constituted more objective results [7].…”