Recognizing Cartoon Image Gestures for Retrieval and Interactive Cartoon Clip Synthesis

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dc.contributor.author Yang, Y
dc.contributor.author Zhuang, Y
dc.contributor.author Tao, D
dc.contributor.author Xu, D
dc.contributor.author Yu, J
dc.contributor.author Luo, J
dc.date.accessioned 2012-02-02T10:33:31Z
dc.date.issued 2010-01
dc.identifier.citation IEEE Transactions on Circuits and Systems for Video Technology, 2010, 20 (12), pp. 1745 - 1756
dc.identifier.issn 1051-8215
dc.identifier.other C1 en_US
dc.identifier.uri http://hdl.handle.net/10453/15246
dc.description.abstract In this paper, we propose a new method to recognize gestures of cartoon images with two practical applications, i.e., content-based cartoon image retrieval and interactive cartoon clip synthesis. Upon analyzing the unique properties of four types of features including global color histogram, local color histogram (LCH), edge feature (EF), and motion direction feature (MDF), we propose to employ different features for different purposes and in various phases. We use EF to define a graph and then refine its local structure by LCH. Based on this graph, we adopt a transductive learning algorithm to construct local patches for each cartoon image. A spectral method is then proposed to optimize the local structure of each patch and then align these patches globally. MDF is fused with EF and LCH and a cartoon gesture space is constructed for cartoon image gesture recognition. We apply the proposed method to content-based cartoon image retrieval and interactive cartoon clip synthesis. The experiments demonstrate the effectiveness of our method.
dc.publisher IEEE
dc.relation.isbasedon 10.1109/TCSVT.2010.2087452
dc.subject Image Gestures, Retrieval, Synthesis, Subspace Learning, Manifold Learning, Artificial Intelligence & Image Processing
dc.subject Image Gestures, Retrieval, Synthesis, Subspace Learning, Manifold Learning; Artificial Intelligence & Image Processing
dc.title Recognizing Cartoon Image Gestures for Retrieval and Interactive Cartoon Clip Synthesis
dc.type Journal Article
dc.parent IEEE Transactions on Circuits and Systems for Video Technology
dc.journal.volume 12
dc.journal.volume 20
dc.journal.number 12 en_US
dc.publocation USA en_US
dc.identifier.startpage 1745 en_US
dc.identifier.endpage 1756 en_US
dc.cauo.name FEIT.A/DRsch Ctr Quantum Computat'n & Intelligent Systs en_US
dc.conference Verified OK en_US
dc.for 0906 Electrical and Electronic Engineering
dc.personcode 0000066519 en_US
dc.personcode 0000066520 en_US
dc.personcode 111502 en_US
dc.personcode 0000066521 en_US
dc.personcode 0000049502 en_US
dc.personcode 0000066522 en_US
dc.percentage 100 en_US
dc.classification.name Electrical and Electronic Engineering en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords Image Gestures, Retrieval, Synthesis, Subspace Learning, Manifold Learning en_US
dc.description.keywords Image Gestures, Retrieval, Synthesis, Subspace Learning, Manifold Learning
pubs.embargo.period Not known
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 - Quantum Computation and Intelligent Systems


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