Title :
Video Frame Identification for Learning Media Content Understanding
Author :
Li, Ying ; Dorai, Chitra
Author_Institution :
IBM Thomas J. Watson Res. Center, Hawthorne, NY
Abstract :
This paper presents our latest work on identifying frame content types for understanding learning media content. In particular, we categorize frames into six classes namely, slide, Web-page, instructor, audience, picture-in-picture and miscellaneous, which make up salient narrative modes in learning videos. Various image and video analysis approaches are explored to achieve this task. Preliminary experiments carried out on three recorded seminars have yielded encouraging results. The identification of fine-grained visual content types can assist us in content understanding, access, browsing and searching of generic learning videos
Keywords :
content-based retrieval; learning (artificial intelligence); video retrieval; video signal processing; fine-grained visual content; generic learning videos; image analysis; media content understanding; video frame identification; Character recognition; Educational institutions; Educational programs; Electronic learning; Face recognition; Histograms; Image analysis; Industrial training; Internet; Seminars;
Conference_Titel :
Multimedia and Expo, 2005. ICME 2005. IEEE International Conference on
Conference_Location :
Amsterdam
Print_ISBN :
0-7803-9331-7
DOI :
10.1109/ICME.2005.1521714