Machine Vision and Applications
A variational level set approach to multiphase motion
Journal of Computational Physics
International Journal of Computer Vision
Minimal Surfaces Based Object Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Vision and Image Understanding
Variational problems and partial differential equations on implicit surfaces
Journal of Computational Physics
Flux Maximizing Geometric Flows
IEEE Transactions on Pattern Analysis and Machine Intelligence
Regularized Laplacian Zero Crossings as Optimal Edge Integrators
International Journal of Computer Vision
Variational principles, surface evolution, PDEs, level set methods, and the stereo problem
IEEE Transactions on Image Processing
Reconstructing Open Surfaces from Image Data
International Journal of Computer Vision
Variational Surface Interpolation from Sparse Point and Normal Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-View Stereo Reconstruction and Scene Flow Estimation with a Global Image-Based Matching Score
International Journal of Computer Vision
Generalized Gradients: Priors on Minimization Flows
International Journal of Computer Vision
Journal of Mathematical Imaging and Vision
Shape from Specular Reflection and Optical Flow
International Journal of Computer Vision
International Journal of Computer Vision
Joint Estimation of Shape and Reflectance using Multiple Images with Known Illumination Conditions
International Journal of Computer Vision
Variational segmentation of image sequences using deformable shape priors
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Variational segmentation using dynamical models for rigid motion
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Converting level set gradients to shape gradients
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
International Journal of Computer Vision
A gradient descent procedure for variational dynamic surface problems with constraints
VLSM'05 Proceedings of the Third international conference on Variational, Geometric, and Level Set Methods in Computer Vision
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Developments within the computer vision community have led to the formulation of many interesting problems in a variational setting. This paper introduces the manifold of admissible surfaces and a scalar product on its tangent spaces. This makes it possible to properly define gradients and gradient descent procedures for variational problems involving m-surfaces. These concepts lead to a geometric understanding of current state of the art evolution methods and steepest descent evolution equations. By geometric reasoning, common procedures within the variational level set framework are explained and justified. Concrete computations for a general class of functionals are presented and applied to common variational problems for curves and surfaces.