Character Identification in Feature-Length Films Using Global Face-Name Matching

Identification of characters in films, although very intuitive to humans, still poses a significant challenge to computer methods. In this paper, we investigate the problem of identifying characters in feature-length films using video and film script. Different from the state-of-the-art methods on n...

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Bibliographic Details
Published in:IEEE transactions on multimedia 2009-11, Vol.11 (7), p.1276-1288
Main Authors: Yi-Fan Zhang, Changsheng Xu, Hanqing Lu, Yeh-Min Huang
Format: Article
Language:English
Subjects:
Applied sciences
Artificial intelligence
Computer science
control theory
systems
Computer systems and distributed systems. User interface
Conductive films
Content based retrieval
Exact sciences and technology
Face detection
Face identification
Face recognition
Humans
Indexing
Information retrieval. Graph
Information systems. Data bases
Laboratories
Memory organisation. Data processing
Motion pictures
movie analysis
Pattern recognition
Pattern recognition. Digital image processing. Computational geometry
social network analysis
Social network services
Software
Theoretical computing
video browsing
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Summary:Identification of characters in films, although very intuitive to humans, still poses a significant challenge to computer methods. In this paper, we investigate the problem of identifying characters in feature-length films using video and film script. Different from the state-of-the-art methods on naming faces in the videos, most of which used the local matching between a visible face and one of the names extracted from the temporally local video transcript, we attempt to do a global matching between names and clustered face tracks under the circumstances that there are not enough local name cues that can be found. The contributions of our work include: 1) A graph matching method is utilized to build face-name association between a face affinity network and a name affinity network which are, respectively, derived from their own domains (video and script). 2) An effective measure of face track distance is presented for face track clustering. 3) As an application, the relationship between characters is mined using social network analysis. The proposed framework is able to create a new experience on character-centered film browsing. Experiments are conducted on ten feature-length films and give encouraging results.
ISSN:1520-9210
1941-0077
DOI:10.1109/TMM.2009.2030629