Proceedings Paper
A machine learning based lecture video segmentation and indexing algorithm| Format | Member Price | Non-Member Price |
|---|---|---|
| $17.00 | $21.00 |
Paper Abstract
Video segmentation and indexing are important steps in multi-media document understanding and information
retrieval. This paper presents a novel machine learning based approach for automatic structuring and indexing
of lecture videos. By indexing video content, we can support both topic indexing and semantic querying of
multimedia documents. In this paper, our proposed approach extracts features from video images and then uses
these features to construct a model to label video frames. Using this model, we are able to segment and indexing
videos with accuracy of 95% on our test collection.
Paper Details
Date Published: 24 March 2014
PDF: 8 pages
Proc. SPIE 9021, Document Recognition and Retrieval XXI, 90210V (24 March 2014); doi: 10.1117/12.2042602
Published in SPIE Proceedings Vol. 9021:
Document Recognition and Retrieval XXI
Bertrand Coüasnon; Eric K. Ringger, Editor(s)
PDF: 8 pages
Proc. SPIE 9021, Document Recognition and Retrieval XXI, 90210V (24 March 2014); doi: 10.1117/12.2042602
Show Author Affiliations
Di Ma, Illinois Institute of Technology (United States)
Bingqing Xie, Illinois Institute of Technology (United States)
Bingqing Xie, Illinois Institute of Technology (United States)
Gady Agam, Illinois Institute of Technology (United States)
Published in SPIE Proceedings Vol. 9021:
Document Recognition and Retrieval XXI
Bertrand Coüasnon; Eric K. Ringger, Editor(s)
© SPIE. Terms of Use
