Anchor person shot detection for news video indexing based on graph-theoretical clustering and fuzzy if-then rules

Xinbo Gao; Qi Li; Jie Li

doi:10.1117/12.539898

25 September 2003 Anchor person shot detection for news video indexing based on graph-theoretical clustering and fuzzy if-then rules

Xinbo Gao, Qi Li, Jie Li

Author Affiliations +

Proceedings Volume 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition; (2003) https://doi.org/10.1117/12.539898
Event: Third International Symposium on Multispectral Image Processing and Pattern Recognition, 2003, Beijing, China

Abstract

Anchorperson shot detection is of significance for video shot semantic parsing and indexing clues extraction in content-based news video indexing and retrieval system. This paper presents a model-free anchorperson shot detection scheme based on the graph-theoretical clustering and fuzzy interference. First, a news video is segmented into video shots with any an effective video syntactic parsing algorithm. For each shot, one frame is extracted from the frame sequence as a representative key frame. Then the graph-theoretical clustering algorithm is performed on the key frames to identify the anchorperson frames. The anchorperson frames are further refined based on face detection and fuzzy interference with if-then rules. The proposed scheme achieves a precision of 98.40% and a recall of over 97.69% in the anchorperson shot detection experiment.

Citation Download Citation

Xinbo Gao, Qi Li, and Jie Li "Anchor person shot detection for news video indexing based on graph-theoretical clustering and fuzzy if-then rules", Proc. SPIE 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition, (25 September 2003); https://doi.org/10.1117/12.539898

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