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.

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; and 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, wherein application of the regression model occurs if the source image is not approximately square, and wherein each of the operations is executed by one or more processors.