Lessons Learned from Building a Terabyte Digital Video Library

The Informedia Project at Carnegie Mellon University has created a terabyte digital video library in which automatically derived descriptors for the video are used for indexing, segmenting and accessing the library contents. Begun in 1994, the project presented numerous challenges for library creation and deployment, valuable information covered in this article. The authors, developers of the project at Carnegie Mellon University, addressed these challenges by: automatically extracting information from digitized video; creating interfaces that allowed users to search for and retrieve videos based on extracted information; and validating the system through user testbeds. Through speech, image, and natural language processing, the Informedia Project has demonstrated that previously inaccessible data can be derived automatically and used to describe and index video segments.

[1]  Michael G. Christel,et al.  Improving Access to a Digital Video Library , 1997, INTERACT.

[2]  Alexander G. Hauptmann,et al.  Speech recognition for a digital video library , 1998 .

[3]  Yihong Gong,et al.  Image indexing and retrieval based on human perceptual color clustering , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[4]  Karen Spärck Jones,et al.  Retrieving spoken documents by combining multiple index sources , 1996, SIGIR '96.

[5]  Wendy E. Mackay,et al.  DIVA: exploratory data analysis with multimedia streams , 1998, CHI.

[6]  Behzad Shahraray,et al.  On the application of multimedia processing to telecommunications , 1997, Proceedings of International Conference on Image Processing.

[7]  Ellen K. Hughes,et al.  Video OCR for digital news archive , 1998, Proceedings 1998 IEEE International Workshop on Content-Based Access of Image and Video Database.

[8]  Atreyi Kankanhalli,et al.  A Video Database System for Digital Libraries , 1994, DL.

[9]  Michael J. Witbrock,et al.  Using words and phonetic strings for efficient information retrieval from imperfectly transcribed spoken documents , 1997, DL '97.

[10]  Michael G. Christel,et al.  Evolving video skims into useful multimedia abstractions , 1998, CHI.

[11]  Behzad Shahraray,et al.  On the applications of multimedia processing to communications , 1998, Proc. IEEE.

[12]  Wolfgang Effelsberg,et al.  Video abstracting , 1997, CACM.

[13]  R. E. Jones,et al.  EXPERIMENTS IN INFORMATION RETRIEVAL FROM SPOKEN DOCUMENTS , 1998 .