Studying aesthetics in photographic images using a computational approach
AssigneeThe Penn State Research Foundation
InventorsRitendra Datta, Jia Li, James Z. Wang
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AssigneeThe Penn State Research Foundation
InventorsRitendra Datta, Jia Li, James Z. Wang
Estimating the term…
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.
A computer-based method of inferring and utilizing aesthetic quality of photographs and other images, comprising the steps of:
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