Title :
Story Boundary Detection in News Video using Global Rule Induction Technique
Author :
Chaisorn, Lekha ; Chua, Tat-Seng
Author_Institution :
Media Div., Inst. for Infocomm. Res., Singapore
Abstract :
Global rule induction technique has been successfully used in information extraction (IE) from text documents. In this paper, we employ the technique to identify story boundaries in news video. We divide our framework into two levels: shot and story levels. We use a hybrid algorithm to classify each input video shot into one of the predefined genre types and employ the global rule induction technique to extract story boundaries from the sequence of classified shots. We evaluate our rule induction based system on ~120-hours of news video provided by TRECVID 2003. The results show that we could achieve an F 1 accuracy of over 75%
Keywords :
feature extraction; image classification; image sequences; video signal processing; global rule induction technique; information extraction; news video sequence; shot classification; story boundard detection; Clustering algorithms; Data mining; Hidden Markov models; Pattern analysis; Performance analysis; System performance; System testing; Tagging; Training data; Video sequences;
Conference_Titel :
Multimedia and Expo, 2006 IEEE International Conference on
Conference_Location :
Toronto, Ont.
Print_ISBN :
1-4244-0366-7
Electronic_ISBN :
1-4244-0367-7
DOI :
10.1109/ICME.2006.262649
