SSVM (Scale Space and Variational Methods in Computer Vision) is a biennial conference devoted to mathematical aspects of Computer Vision and Image Analysis in general. It focuses on multiscale representation of image contents and also on processing and analysis methods using Partial Differential Equations (PDEs), The Calculus of Variation, infinite and finite dimensional optimization problems. They are strongly overlapping topics, as, for instance, multiscale representation is often associated to special PDEs, and the calculus of variations is a large source of PDEs. The methods on which SSVM focuses are essential to extraction of relevant information in the very high dimensional data that images are. They find applications in a range of disciplines, for instance diagnostic imaging, micro-geological analysis, robot vision, etc.
Since its start, SSVM has been a forum where mathematicians, computer scientists and vision scientists have met and exchanged research experiences within the fields of computer vision and image analysis, and all working on the intersection of Computer Science and Applied Mathematics. Interest range goes from basic research such as understanding of image structure, its links to human perception, to complex tasks such as segmentation, reconstruction, etc.
Conference topics include, but are not limited to:
Level sets methods
PDEs in image processing
Inverse problems in imaging
Optimization methods in imaging
Convex and non convex modeling and optimization in imaging
Restoration and reconstruction
Multi-scale shape analysis
3D imaging modalities
Wavelets and image decomposition
Shape from X
Selection of salient scales
Expected price: EUR 1000
Time: 2:15 pm to 2:00 pm