WebSEEK, A Content-Based Image and Video Search and Catalog Tool for the Web. WebSEEk is a content-based image and video catalog and search tool for the World Wide Web. WebSEEK collects the images and videos using several autonomous Web agents which automatically analyze, index, and assign the images and videos to subject classes. The system is novel in that it utilizes text and visual information synergistically to provide for cataloging and searching for the images and videos. The complete system possesses several powerful functionalities, namely, searching using image content-based techniques, query modification using content-based relevance feedback, automated collection of visual information, compact presentation of images and videos for displaying query results, image and video subject search and navigation, text-based searching, and search results lists manipulations such as intersection, subtraction and concatenation. At present, the system has catalogued over 650,000 images and 10,000 videos from the Web. We have also developed techniques for automatic categorization of new unconstrained images/video to semantic-level subject classes in the image taxonomy. A working image taxonomy has been constructed in a semi-automatic way in the current prototype of WebSEEk. The categorization algorithms explore optimal integration of visual features (such as color, texture, spatial layout) and text features (such as associated html tags, captions, and articles).

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  1. Zhuang, Yi; Jiang, Nan; Wu, Zhiang; Li, Qing; Chiu, Dickson K. W.; Hu, Hua: Efficient and robust large medical image retrieval in mobile cloud computing environment (2014) ioport
  2. Di Mascio, Tania; Frigioni, Daniele; Tarantino, Laura: VISTO: a new CBIR system for vector images (2010) ioport
  3. Chen, Yixin; Li, Jia; Wang, James Z.: Machine learning and statistical modeling approaches to image retrieval. (2004)