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A Hitherto Unnoticed Singularity of Scale-Space
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Displacement Estimates Through Adaptive Affinities
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Computation of component image velocity from local phase information
International Journal of Computer Vision
Mathematica: a system for doing mathematics by computer (2nd ed.)
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Performance of optical flow techniques
International Journal of Computer Vision
The Intrinsic Structure of Optic Flow Incorporating Measurement Duality
International Journal of Computer Vision
Feature Detection with Automatic Scale Selection
International Journal of Computer Vision
The Topological Structure of Scale-Space Images
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Image Registration Using Wavelet-Based Motion Model
International Journal of Computer Vision
Scale-Space Theory in Computer Vision
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International Journal of Computer Vision
What Do Features Tell about Images?
Scale-Space '01 Proceedings of the Third International Conference on Scale-Space and Morphology in Computer Vision
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
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A linear image reconstruction framework based on sobolev type inner products
Scale-Space'05 Proceedings of the 5th international conference on Scale Space and PDE Methods in Computer Vision
Variational optical flow computation in real time
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3D winding number: theory and application to medical imaging
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Cardiac motion estimation using covariant derivatives and helmholtz decomposition
STACOM'11 Proceedings of the Second international conference on Statistical Atlases and Computational Models of the Heart: imaging and modelling challenges
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Optic flow describes the apparent motion that is present in an image sequence. We show the feasibility of obtaining optic flow from dynamic properties of a sparse set of multi-scale anchor points. Singular points of a Gaussian scale space image are identified as feasible anchor point candidates and analytical expressions describing their dynamic properties are presented. Advantages of approaching the optic flow estimation problem using these anchor points are that (i) in these points the notorious aperture problem does not manifest itself, (ii) it combines the strengths of variational and multi-scale methods, (iii) optic flow definition becomes independent of image resolution, (iv) computations of the components of the optic flow field are decoupled and that (v) the feature set inducing the optic flow field is very sparse (typically $