Automatic Thumbnail Cropping and its Effectiveness

Abstract

Thumbnail images provide users of image retrieval and browsing systems with a method for quickly scanning large numbers of images. Recognizing the objects in an image is important in many retrieval tasks, but thumbnails generated by shrinking the original image often render objects illegible. We study the ability of computer vision systems to detect key components of images so that intelligent cropping, prior to shrinking, can render objects more recognizable. We evaluate automatic cropping techniques 1) based on a method that detects salient portions of general images, and 2) based on automatic face detection. Our user study shows that these methods result in small thumbnails that are substantially more recognizable and easier to find in the context of visual search. Keywords: Saliency map, thumbnail, image cropping, face detection, usability study, visual search, zoomable user interfaces UMIACS-TR-2003-39 HCIL-TR-2003-13