Image cropping using supervised learning

A computer-readable storage medium, that is non-transitory, storing a program, wherein the program, when executed, instructs a processor to perform the following operations:

• extract a plurality of pixel-level features from each of a plurality of source images, wherein each of the source images is associated with a thumbnail created by an editor;
• generating a plurality of unique bounding boxes for each source image;
• calculate a plurality of region-level features for each bounding box, wherein each region-level feature results from the aggregation of pixel values for one of the pixel-level features;
• learn a regression model, using at least the calculated region-level features and the thumbnail associated with the source image;
• choose a thumbnail from a plurality of unique bounding boxes in a new image, based at least in part on application of the regression model;
• and
• use a thumbnail received from an editor instead of the chosen thumbnail, if the chosen thumbnail is of insufficient quality as measured against a scoring threshold, wherein a center-fit approach is applied to the source image to obtain a thumbnail, if the source image is approximately square.

A method for generating thumbnail images, comprising the operations of:

• extracting a plurality of disaggregated features from each of a plurality of source images, wherein each of the source images is associated with a thumbnail created by an editor;
• generating a plurality of unique bounding boxes for each source image;
• calculate a plurality of region-level features for each bounding box, wherein each of these region-level feature results from the aggregation of values for one of the disaggregated features;
• determining another region-level feature for each bounding box;
• learning a regression model, using at least the calculated region-level features, the other region-level feature, and the thumbnail associated with the source image;
• choosing a thumbnail from a plurality of candidate regions in a new image, based at least in part on application of the regression model;
• and
• using a thumbnail received from an editor instead of the chosen thumbnail, if the chosen thumbnail is of insufficient quality as measured against a scoring threshold, wherein a center-fit approach is applied to the source image to obtain a thumbnail, if the source image is approximately square, and wherein each of the operations is executed by one or more processors.