Studying aesthetics in photographic images using a computational approach

摘要

The aesthetic quality of a picture is automatically inferred using visual content as a machine learning problem using, for example, a peer-rated, on-line photo sharing Website as data source. Certain visual features of images are extracted based on the intuition that they can discriminate between aesthetically pleasing and displeasing images. A one-dimensional support vector machine is used to identify features that have noticeable correlation with the community-based aesthetics ratings. Automated classifiers are constructed using the support vector machines and classification trees, with a simple feature selection heuristic being applied to eliminate irrelevant features. Linear regression on polynomial terms of the features is also applied to infer numerical aesthetics ratings.

主权项

1. A computer-based method of inferring and utilizing aesthetic quality of photographs and other images, comprising the steps of:
receiving a plurality of digitized images along with aesthetic-based ratings of the images; performing one or more software operations on the digitized images to automatically extract a plurality of visual features representative of each image; receiving an image without an aesthetic-based rating; automatically extracting a plurality of visual features representative of the received image; computing a familiarity measure for the received image by correlating the visual features extracted from the received image to the visual features extracted from the other images; determining an aesthetic-based rating for the received image on the basis of the familiarity measure, wherein a lower familiarity is indicative of originality and a higher rating; and using one or more statistical methods to correlate the extracted visual features and the aesthetic-based ratings to classify the images on the basis of aesthetic value, rate the images on a scale relating to aesthetics value, or select/eliminate an image based upon aesthetic quality.