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Web-Scale Image Retrieval and Its Novel Applications

Content-based image retrieval has been studied more than two decades, but surprisingly has not been widely deployed for web-scale image databases. This is mainly caused by two factors: low scalability and lack of commercial applications. In this poster we review our recent research activities for developing web-scalable image retrieval and its novel applications to address various problems. First we discuss scalability issues to be addressed for handling web-scale image databases. We also describe our hashing technique to drastically lower down the memory and computational requirements for web-scale image retrieval. Second we explain its applications to the fields of image copyright and editing, and discuss benefits that it brings over prior techniques developed without considering or utilizing web-scale image databases. Finally, we discuss remained problems towards our goal.