News story segmentation based on audio-visual features fusion

Author

Song, Yu ; Wang, Wenhong ; Guo, Fengjuan

Author_Institution

Dept. of Comput., North China Electr. Power Univ., Baoding, China

fYear

2009

fDate

25-28 July 2009

Firstpage

1065

Lastpage

1068

Abstract

This paper presents a method for news video story segmentation, which fuses multi-feature including audio and visual. At first, this paper detects the anchorperson shot for news video and determines the beginning of news story, and then detects topic caption between anchorperson shots. In the next step, silence clips in news video are detected using short-time energy and short-time average zero-crossing rate parameters, and then voice features of anchorperson is analyzed. At last, this method fuses multi-feature such as anchorperson shot, topic caption, silence and voice feature to segment news stories. Experimental results show that the approach is valid and avoid the deficiency of detecting news story by a single feature.

Keywords

image segmentation; video signal processing; audio-visual features fusion; news story segmentation; news video; short-time average zero-crossing rate parameters; short-time energy; Broadcasting; Computer science; Computer science education; Educational technology; Fuses; Gunshot detection systems; Hidden Markov models; Image segmentation; Layout; Multimedia communication; audio-visual fusion; news video; shot detection; silence clip; story segmentation;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science & Education, 2009. ICCSE '09. 4th International Conference on

Conference_Location

Nanning

Print_ISBN

978-1-4244-3520-3

Electronic_ISBN

978-1-4244-3521-0

Type

conf

DOI

10.1109/ICCSE.2009.5228544

Filename

5228544