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Automatic Thumbnail Cropping and its Effectiveness

dc.contributor.authorSuh, Bongwonen_US
dc.contributor.authorLing, Haibinen_US
dc.contributor.authorBederson, Benjamin B.en_US
dc.contributor.authorJacobs, David W.en_US
dc.description.abstractThumbnail 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-2003-13en_US
dc.format.extent1094680 bytes
dc.relation.ispartofseriesUM Computer Science Department; CS-TR-4469en_US
dc.relation.ispartofseriesUMIACS; UMIACS-TR-2003-39en_US
dc.titleAutomatic Thumbnail Cropping and its Effectivenessen_US
dc.typeTechnical Reporten_US
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_US
dc.relation.isAvailableAtUniversity of Maryland (College Park, Md.)en_US
dc.relation.isAvailableAtTech Reports in Computer Science and Engineeringen_US
dc.relation.isAvailableAtUMIACS Technical Reportsen_US

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