Tour into the picture: using a spidery mesh interface to make animation from a single image
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Teddy: a sketching interface for 3D freeform design
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
International Journal of Computer Vision
Finite-Element Methods for Active Contour Models and Balloons for 2-D and 3-D Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Convex Optimization
"GrabCut": interactive foreground extraction using iterated graph cuts
ACM SIGGRAPH 2004 Papers
ACM SIGGRAPH 2005 Papers
Single View Reconstruction of Curved Surfaces
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
FiberMesh: designing freeform surfaces with 3D curves
ACM SIGGRAPH 2007 papers
An Experimental Comparison of Discrete and Continuous Shape Optimization Methods
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Continuous Global Optimization in Multiview 3D Reconstruction
International Journal of Computer Vision
Non-parametric Single View Reconstruction of Curved Objects Using Convex Optimization
Proceedings of the 31st DAGM Symposium on Pattern Recognition
Image-based 3D modeling via Cheeger sets
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
Repoussé: automatic inflation of 2D artwork
SBM'08 Proceedings of the Fifth Eurographics conference on Sketch-Based Interfaces and Modeling
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We explore the 3D reconstruction of objects from a single view within an interactive framework by using silhouette information. In order to deal with the highly ill-posed nature of the problem we propose two different reconstruction priors: a shape and a volume prior and cast them into a variational problem formulation. For both priors we show that the corresponding relaxed optimization problem is convex. This leads to unique solutions which are independent of initialization and which are either globally optimal (shape prior) or can be shown to lie within bounds from the optimal solution (volume prior). We analyze properties of the proposed priors with regard to the reconstruction results as well as their impact on the minimization problem. By employing an implicit volumetric representation our reconstructions enjoy complete topological freedom. Being parameter-based, our interactive reconstruction tool allows for intuitive and easy to use modeling of the reconstruction result.