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231224s2018 xx |||||o 00| ||eng c |
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|a 10.1109/TVCG.2017.2657511
|2 doi
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|a pubmed24n0894.xml
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|a DE-627
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|e rakwb
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|a eng
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|a Yang, Wenwu
|e verfasserin
|4 aut
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|a Context-Aware Computer Aided Inbetweening
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|c 2018
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
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|2 rdamedia
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|a ƒa Online-Ressource
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|a Date Completed 28.01.2019
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|a Date Revised 28.01.2019
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a This paper presents a context-aware computer aided inbetweening (CACAI) technique that interpolates planar strokes to generate inbetween frames from a given set of key frames. The inbetweening is context-aware in the sense that not only the stroke's shape but also the context (i.e., the neighborhood of a stroke) in which a stroke appears are taken into account for the stroke correspondence and interpolation. Given a pair of successive key frames, the CACAI automatically constructs the stroke correspondence between them by exploiting the context coherence between the corresponding strokes. Meanwhile, the construction algorithm is able to incorporate the user's interaction with ease and allows the user more effective control over the correspondence process than existing stroke matching techniques. With a one-to-one stroke correspondence, the CACAI interpolates the shape and context between the corresponding strokes for the generation of intermediate frames. In the interpolation sequence, both the shape of individual strokes and the spatial layout between them are well retained such that the feature characteristics and visual appearance of the objects in the key frames can be fully preserved even when complex motions are involved in these objects. We have developed a prototype system to demonstrate the ease of use and effectiveness of the CACAI
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|a Journal Article
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|a Research Support, Non-U.S. Gov't
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|i Enthalten in
|t IEEE transactions on visualization and computer graphics
|d 1996
|g 24(2018), 2 vom: 04. Feb., Seite 1049-1062
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|g volume:24
|g year:2018
|g number:2
|g day:04
|g month:02
|g pages:1049-1062
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|u http://dx.doi.org/10.1109/TVCG.2017.2657511
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