Abstract: Techniques related to no-reference image and video quality evaluation are discussed. Such techniques may include generating, for a still image or video frame, features including a natural scene statistics based feature and an image quality based feature and determining an image evaluation indicator associated with the still image or video frame based on a mapping of the generated features to the image evaluation indicator.

Abstract: Techniques related to no-reference image and video quality evaluation are discussed. Such techniques may include generating, for a still image or video frame, features including a natural scene statistics based feature and an image quality based feature and determining an image evaluation indicator associated with the still image or video frame based on a mapping of the generated features to the image evaluation indicator.

Abstract: A method that includes classifying photographs into categories; generating computational models of image aesthetics, each computational model of image aesthetics associated to one different category of the categories; extracting a plurality of features from a photograph, the plurality of features including simplicity features, global features computed in the whole image and/or low-level features in contrasting regions of an image of the photograph, the contrasting regions being partitions of the image obtained by applying an image segmentation algorithm based on feature contrast to the photograph; and applying a computational model of image aesthetics to at least part of the plurality of features extracted from the photograph, the computational model applied according to the category of the photograph, in order to assess aesthetic quality of the photograph.

Abstract: A method to assess aesthetic quality of photographs, including classifying photographs into categories; generating computational models of image aesthetics, each computational model of image aesthetics associated to one different category of the categories; extracting a plurality of features from a photograph, the plurality of features being simplicity features, global features computed in the whole image and/or low-level features in contrasting regions of an image of said photograph. The contrasting regions are partitions of the image obtained by applying an image segmentation algorithm based on feature contrast to the photograph. The method also including applying a computational model of image aesthetics to at least part of the plurality of features extracted from said photograph, the computational model applied according to the category of the photograph, in order to assess aesthetic quality of the photograph.