Retrieval based interactive cartoon synthesis via unsupervised bi-distance metric learning

Yang, Y; Zhuang, Y; Xu, D; Pan, Y; Tao, D; Maybank, S

Retrieval based interactive cartoon synthesis via unsupervised bi-distance metric learning

Yang, Y

Zhuang, Y Xu, D Pan, Y Tao, D

Maybank, S

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Publication Type:: Conference Proceeding
Citation:: MM'09 - Proceedings of the 2009 ACM Multimedia Conference, with Co-located Workshops and Symposiums, 2009, pp. 311 - 320
Issue Date:: 2009-12-28

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Field	Value	Language
dc.contributor.author	Yang, Y https://orcid.org/0000-0001-5528-0546	en_US
dc.contributor.author	Zhuang, Y	en_US
dc.contributor.author	Xu, D	en_US
dc.contributor.author	Pan, Y	en_US
dc.contributor.author	Tao, D https://orcid.org/0000-0001-7225-5449	en_US
dc.contributor.author	Maybank, S	en_US
dc.date.issued	2009-12-28	en_US
dc.identifier.citation	MM'09 - Proceedings of the 2009 ACM Multimedia Conference, with Co-located Workshops and Symposiums, 2009, pp. 311 - 320	en_US
dc.identifier.isbn	9781605586083	en_US
dc.identifier.uri	http://hdl.handle.net/10453/17619
dc.description.abstract	Cartoons play important roles in many areas, but it requires a lot of labor to produce new cartoon clips. In this paper, we propose a gesture recognition method for cartoon character images with two applications, namely content-based cartoon image retrieval and cartoon clip synthesis. We first define Edge Features (EF) and Motion Direction Features (MDF) for cartoon character images. The features are classified into two different groups, namely intra-features and inter-features. An Unsupervised Bi-Distance Metric Learning (UBDML) algorithm is proposed to recognize the gestures of cartoon character images. Different from the previous research efforts on distance metric learning, UBDML learns the optimal distance metric from the heterogeneous distance metrics derived from intra-features and inter-features. Content-based cartoon character image retrieval and cartoon clip synthesis can be carried out based on the distance metric learned by UBDML. Experiments show that the cartoon character image retrieval has a high precision and that the cartoon clip synthesis can be carried out efficiently. Copyright 2009 ACM.	en_US
dc.relation.ispartof	MM'09 - Proceedings of the 2009 ACM Multimedia Conference, with Co-located Workshops and Symposiums	en_US
dc.relation.isbasedon	10.1145/1631272.1631316	en_US
dc.title	Retrieval based interactive cartoon synthesis via unsupervised bi-distance metric learning	en_US
dc.type	Conference Proceeding
utslib.for	080109 Pattern Recognition and Data Mining	en_US
dc.location.activity	Beijing, China	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Cartoons play important roles in many areas, but it requires a lot of labor to produce new cartoon clips. In this paper, we propose a gesture recognition method for cartoon character images with two applications, namely content-based cartoon image retrieval and cartoon clip synthesis. We first define Edge Features (EF) and Motion Direction Features (MDF) for cartoon character images. The features are classified into two different groups, namely intra-features and inter-features. An Unsupervised Bi-Distance Metric Learning (UBDML) algorithm is proposed to recognize the gestures of cartoon character images. Different from the previous research efforts on distance metric learning, UBDML learns the optimal distance metric from the heterogeneous distance metrics derived from intra-features and inter-features. Content-based cartoon character image retrieval and cartoon clip synthesis can be carried out based on the distance metric learned by UBDML. Experiments show that the cartoon character image retrieval has a high precision and that the cartoon clip synthesis can be carried out efficiently. Copyright 2009 ACM.

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http://hdl.handle.net/10453/17619