An Effective News Anchorperson Shot Detection Method Based on Adaptive Audio/Visual Model Generation

• Published in: Image and Video Retrieval pp. 276 - 285
• Main Authors: Kim, Sang-Kyun, Hwang, Doo Sun, Kim, Ji-Yeun, Seo, Yang-Seock
• Format: Book Chapter Conference Proceeding
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2005; Springer
• Series: Lecture Notes in Computer Science
• Subjects: Applied sciences; Artificial intelligence; Audio Feature; Audio Signal; Computer science; control theory; systems; Exact sciences and technology; False Alarm; News Program; News Video; Pattern recognition. Digital image processing. Computational geometry; Adaptive detection; Modal analysis; Segmentation; Image processing; Video signal; Information retrieval; Modeling; Adaptive method; Information use; Silence; Narrative; Audio acoustics; Program proof; Program test; Visual information; Voice
• ISBN: 9783540278580; 3540278583
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/11526346_31

A multi-modal method to improve the performance of the anchorperson shot detection for news story segmentation is proposed in this paper. The anchorperson voice information is used for the verification of anchorperson shot candidates extracted by visual information. The algorithm starts with the anchorperson voice shot candidate extraction using time and silence condition. The anchorperson templates are generated from the anchorperson face and cloth information from the anchorperson voice shots extracted. The anchorperson voice models are then created after segregating anchorperson voice shots containing 2 or more voices. The anchorperson voice model verifies the anchorperson shot candidates obtained from visual information. 720 minutes of news programs are tested and experimental results are demonstrated.