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  5. Roto++: accelerating professional rotoscoping using shape manifolds
 
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Roto++: accelerating professional rotoscoping using shape manifolds
File(s)
rotopp_full.pdf (17.68 MB)
Accepted version
OA Location
http://visual.cs.ucl.ac.uk/pubs/rotopp/rotopp_full.pdf
Author(s)
Li, W
Viola, F
Starck, J
Brostow, GJ
Campbell, NDF
Type
Journal Article
Abstract
Rotoscoping (cutting out different characters/objects/layers in raw video footage) is a ubiquitous task in modern post-production and represents a significant investment in person-hours. In this work, we study the particular task of professional rotoscoping for high-end, live action movies and propose a new framework that works with roto-artists to accelerate the workflow and improve their productivity. Working with the existing keyframing paradigm, our first contribution is the development of a shape model that is updated as artists add successive keyframes. This model is used to improve the output of traditional interpolation and tracking techniques, reducing the number of keyframes that need to be specified by the artist. Our second contribution is to use the same shape model to provide a new interactive tool that allows an artist to reduce the time spent editing each keyframe. The more keyframes that are edited, the better the interactive tool becomes, accelerating the process and making the artist more efficient without compromising their control. Finally, we also provide a new, professionally rotoscoped dataset that enables truly representative, real-world evaluation of rotoscoping methods. We used this dataset to perform a number of experiments, including an expert study with professional roto-artists, to show, quantitatively, the advantages of our approach.
Date Issued
2016-07-11
Date Acceptance
2016-07-01
Citation
ACM Transactions on Graphics, 2016, 35 (4), pp.1-15
URI
http://hdl.handle.net/10044/1/53922
DOI
https://www.dx.doi.org/10.1145/2897824.2925973
ISSN
0730-0301
Publisher
ACM
Start Page
1
End Page
15
Journal / Book Title
ACM Transactions on Graphics
Volume
35
Issue
4
Copyright Statement
© 2016 Copyright held by the owner/author(s). Publication rights licensed to ACM.
Subjects
0801 Artificial Intelligence And Image Processing
0806 Information Systems
Software Engineering
Publication Status
Published
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