Shape from suggestive contours using 3D priors

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Proceedings title2012 Ninth Conference on Computer and Robot Vision (CRV)
Conference2012 9th Conference on Computer and Robot Vision, CRV 2012, May 28-30, 2012, Toronto, ON, Canada
Article number6233147
Pages236243; # of pages: 8
SubjectDeformable object; Functional mapping; Non-Photorealistic Rendering; Shape inference; statistical priors; suggestive contours; Synthetic experiments; Three-dimensional shape; Computer graphics; Drawing (graphics); Experiments; Forecasting; Photography; Computer vision
AbstractThis paper introduces an approach to predict the three-dimensional shape of an object belonging to a specific class of shapes shown in an input image. We use suggestive contour, a shape-suggesting image feature developed in computer graphics in the context of non-photorealistic rendering, to reconstruct 3D shapes. We learn a functional mapping from the shape space of suggestive contours to the space of 3D shapes and use this mapping to predict 3D shapes based on a single input image. We demonstrate that the method can be used to predict the shape of deformable objects and to predict the shape of human faces using synthetic experiments and experiments based on artist drawn sketches and photographs.
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AffiliationNational Research Council Canada (NRC-CNRC); Information and Communication Technologies
Peer reviewedYes
NPARC number21269268
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Record identifierf392a5eb-7160-4b97-bf61-ca940afe30a4
Record created2013-12-12
Record modified2016-05-09
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