10.7 Case Study of the CMU Digital Library Architecture

The CMU Digital Library architecture, like the Stanford initiative, is outcome of a DLI supported (National Science Foundation funded) project. However, this architecture is, in its current state, more scalable but less function-rich than that of the Stanford except for its video-object support which is one of the best in its category (Banerjee 2004).

CMU's Informedia goal is to achieve machine understanding of video and film media, including all aspects of search, retrieval, visualization and summarization in both contemporaneous and archival content collections. The base technology developed under Informedia-I combines speech, image and natural language understanding to automatically transcribe, segment and index linear video for intelligent search and image retrieval. Informedia-II seeks to improve the dynamic extraction, summarization, visualization, and presentation of distributed video, automatically producing "collages" and "auto-documentaries" that summarize documents from text, images, audio and video into one single abstraction (Carnegie Mellon University 2009).