Abstract
Carnegie Mellon's Informedia Digital Video Library project will establish a large, on-line digital video library featuring full-content and knowledge-based search and retrieval. Intelligent, automatic mechanisms will be developed to populate the library. Search and retrieval from digital video, audio, and text libraries will take place via desktop computer over local, metropolitan, and wide-area networks. The project's approach applies several techniques for content-based searching and video-sequence retrieval. Content is conveyed in both the narrative (speech and language) and the image. Only by the collaborative interaction of image, speech, and natural language understanding technology is it possible to successfully populate, segment, index, and search diverse video collections with satisfactory recall and precision. This collaborative interaction approach uniquely compensates for problems of interpretation and search in error-ridden and ambiguous data sets. The authors have focused the work on two corpuses. One is science documentaries and lectures, the other is broadcast news content with partial closed-captions. Further work will continue to improve the accuracy and performance of the underlying processing as well as explore performance issues related to Web-based access and interoperability with other digital video resources.
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