Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Finite-Element Methods for Active Contour Models and Balloons for 2-D and 3-D Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Priors for Level Set Representations
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Nonlinear Shape Statistics in Mumford-Shah Based Segmentation
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Gradient Vector Flow: A New External Force for Snakes
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
VLSM '01 Proceedings of the IEEE Workshop on Variational and Level Set Methods (VLSM'01)
Gradient flows and geometric active contour models
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Geometric Level Set Methods in Imaging,Vision,and Graphics
Geometric Level Set Methods in Imaging,Vision,and Graphics
Theory for Variational Area-Based Segmentation Using Non-Quadratic Penalty Functions
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
IEEE Transactions on Image Processing
Filling-in by joint interpolation of vector fields and gray levels
IEEE Transactions on Image Processing
Variational optical flow computation in real time
IEEE Transactions on Image Processing
From Inpainting to Active Contours
International Journal of Computer Vision
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We introduce a novel type of region based active contour using image inpainting. Usual region based active contours assume that the image is divided into several semantically meaningful regions and attempt to differentiate them through recovering dynamically statistical optimal parameters for each region. In case when perceptually distinct regions have similar intensity distributions, the methods mentioned above fail. In this work, we formulate the problem as optimizing a ”background disocclusion” criterion, a disocclusion that can be performed by inpainting. We look especially at a family of inpainting formulations that includes the Chan and Shen Total Variation Inpainting (more precisely a regularization of it). In this case, the optimization leads formally to a coupled contour evolution equation, an inpainting equation, as well as a linear PDE depending on the inpainting. The contour evolution is implemented in the framework of level sets. Finally, the proposed method is validated on various examples.