Why meaningful automatic tagging of images is very hard
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Web image interpretation: semi-supervised mining annotated words
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
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Indexing and retrieving large quantities of image data is an extremely challenging and increasingly topical problem for both industry and academia. Massive volumes of image data are all around us-in personal and commercial collections and on public Websites accessible via the Internet. According to a recent study by the market researcher IDC, digital camera sales rose 15 percent in 2006 to 105.7 million units worldwide. A four-year old online photo sharing website, Flickr, has more than 40 million monthly visitors and 2 billion photos uploaded; in fact, in a single day, a few million photos are uploaded. These developments have spurred enormous interest in digital images and a corresponding demand, both from the public and from industry, for better ways of cataloging, annotating, and accessing these data. This in turn has motivated researchers in pattern analysis and machine intelligence to address these tasks. Indeed, in a recent survey of the field of image annotation and retrieval, Wang et al. noticed an exponential growth over the last 10 years in the number of publications arising from researchers in computer vision, database management, machine learning, mathematical statistics, and signal and image processing.