A Hierarchical and Multi-Model Based Algorithm for Lead Detection and News Program Narrative Parsing
19th International Conference on Advanced Information Networking and Applications (AINA'05) Volume 1 (AINA papers) (2005)
Mar. 25, 2005 to Mar. 30, 2005
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AINA.2005.27
Jin-Hau Kuo , National Taiwan University
Jen-Bin Kuo , National Taiwan University
Hsuan-Wei Chen , National Taiwan University
Ja-Ling Wu , National Taiwan University
In this paper, a hierarchical and multi-modal based news item detection algorithm, which can be viewed as a mid-stage solution between the single-modal and the semantic-based approaches, is proposed for parsing TV news program videos. We investigate the production model of TV news program first and then make use of the so-obtained domain knowledge to develop the proposed algorithm. With the add of multi-modal features, such as volume and zero crossing rate in audios and key frame and human face in videos, the proposed algorithm showed rather satisfactory results in both precision and recall measures for parsing a 6-hour news program test video.
J. Kuo, H. Chen, J. Wu and J. Kuo, "A Hierarchical and Multi-Model Based Algorithm for Lead Detection and News Program Narrative Parsing," 19th International Conference on Advanced Information Networking and Applications (AINA'05) Volume 1 (AINA papers)(AINA), Taipei, Taiwan, 2005, pp. 511-514.