SSVM is a biannual meeting within the area of Computer Vision and Image Analysis.
SSVM focuses especially on Multiscale analysis of Image Content, Partial Differential equations, Variational Methods and Optimization.

Contributions are on the form of full papers, 12 pages on Springer LNCS formats, including bibliography, where the proceedings of the conference will be published.

Conference topics include the following areas:
Image analysis Scale-space methods
Level sets methods PDEs in image processing
Inverse problems in imaging Compressed sensing
Optimization methods in imaging Convex and non convex modeling and optimization in imaging
Restoration and reconstruction
Multi-scale shape analysis
3D imaging modalities
3D vision
Wavelets and image decomposition
Segmentation
Stereo reconstruction
Optical flow
Motion estimation Registration
Surface modeling
Implicit surfaces
Shape from X
Inpainting
Color enhancement
Perceptual grouping
Selection of salient scales
Feature analysis
Cross-scale structure
Multi-Orientation Analysis
Differential geometry and Invariants
Mathematics of novel imaging methods
Sub-Riemannian geometry
Medical imaging