Image Cropping Using Supervised Learning

摘要

Software for supervised learning extracts a set of pixel-level features from each source image in collection of source images. Each of the source images is associated with a thumbnail created by an editor. The software also generates a collection of unique bounding boxes for each source image. And the software calculates a set of region-level features for each bounding box. Each region-level feature results from the aggregation of pixel values for one of the pixel-level features. The software learns a regression model, using the calculated region-level features and the thumbnail associated with the source image. Then the software chooses a thumbnail from a collection of unique bounding boxes in a new image, based on application of the regression model. The software uses 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.

主权项

1. A method for generating thumbnail images, comprising the operations of:
extracting 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; calculating 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; learning a regression model, using at least the calculated region-level features and the thumbnail associated with the source image; choosing 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 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 each of the operations is executed by one or more processors.