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Produktbild: Scale Space Methods in Computer Vision
Band 2695

Scale Space Methods in Computer Vision 4th International Conference, Scale-Space 2003, Isle of Skye, UK, June 10-12, 2003, Proceedings

Aus der Reihe Lecture Notes in Computer Science

Fr. 73.90

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

27.05.2003

Herausgeber

Lewis D. Griffin + weitere

Verlag

Springer Berlin

Seitenzahl

819

Maße (L/B/H)

24/15.6/3.4 cm

Gewicht

1180 g

Auflage

2003

Sprache

Englisch

ISBN

978-3-540-40368-5

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

27.05.2003

Herausgeber

Verlag

Springer Berlin

Seitenzahl

819

Maße (L/B/H)

24/15.6/3.4 cm

Gewicht

1180 g

Auflage

2003

Sprache

Englisch

ISBN

978-3-540-40368-5

Herstelleradresse

Springer-Verlag GmbH
Heidelberger Platz 3
14197 Berlin
Deutschland
Email: sdc-bookservice@springer.com
Url: www.springer.com
Telephone: +49 30 827870
Fax: +49 30 8214091

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  • Produktbild: Scale Space Methods in Computer Vision
  • Deep Structure Representation.- On Manifolds in Gaussian Scale Space.- Many-to-Many Matching of Scale-Space Feature Hierarchies Using Metric Embedding.- Content Based Image Retrieval Using Multiscale Top Points.- Feature Coding with a Statistically Independent Cortical Representation.- Scale Space Mathematics.- Scale-Space Image Analysis Based on Hermite Polynomials Theory.- A Complete System of Measurement Invariants for Abelian Lie Transformation Groups.- Equivalences.- Equivalence Results for TV Diffusion and TV Regularisation.- Correspondences between Wavelet Shrinkage and Nonlinear Diffusion.- Implementing Scale Spaces.- Approximating Non-linear Diffusion.- A Generalized Discrete Scale-Space Formulation for 2-D and 3-D Signals.- Real-Time Scale Selection in Hybrid Multi-scale Representations.- ‘Minimal’ Approaches.- A Scale Space for Contour Registration Using Minimal Surfaces.- The Extrema Edges.- Other Evolution Equations.- The Maximum Principle for Beltrami Color Flow.- The Monogenic Scale Space on a Bounded Domain and Its Applications.- Using the Complex Ginzburg-Landau Equation for Digital Inpainting in 2D and 3D.- Local Structure.- Least Squares and Robust Estimation of Local Image Structure.- Regularity Classes for Locally Orderless Images.- Mode Estimation Using Pessimistic Scale Space Tracking.- Image Models.- Properties of Brownian Image Models in Scale-Space.- Image Decomposition Application to SAR Images.- Morphological Scale Space.- Basic Morphological Operations, Band-Limited Images and Sampling.- An Explanation for the Logarithmic Connection between Linear and Morphological Systems.- Temporal Scale Spaces.- Temporal Scale Spaces.- Temporal Structure Tree in Digital Linear Scale Space.- Interest Point Detection and Scale Selection in Space-Time.- Shape.- Towards Recognition-Based Variational Segmentation Using Shape Priors and Dynamic Labeling.- PDE Based Shape from Specularities.- A Markov Random Field Approach to Multi-scale Shape Analysis.- Motion & Stereo.- Variational Dense Motion Estimation Using the Helmholtz Decomposition.- Regularizing a Set of Unstructured 3D Points from a Sequence of Stereo Images.- Poster Session 1.- Image Reconstruction from Multiscale Critical Points.- Texture Classification through Multiscale Orientation Histogram Analysis.- ? Scale Spaces on a Bounded Domain.- Efficient Beltrami Flow Using a Short Time Kernel.- Evolution of the Critical Points in the Curvature and Affine Morphological Scale Spaces.- MAPS: Multiscale Attention-Based PreSegmentation of Color Images.- Convex Colour Sieves.- Scale-Space on Image Profiles about an Object Boundary.- Iris Feature Extraction and Matching Based on Multiscale and Directional Image Representation.- Fast Computation of Scale Normalised Gaussian Receptive Fields.- A Multiphase Level Set Framework for Motion Segmentation.- Segmentation of Coarse and Fine Scale Features Using Multi-scale Diffusion and Mumford-Shah.- On the Number of Modes of a Gaussian Mixture.- Poster Session 2.- Fully Automatic Segmentation of MRI Brain Images Using Probabilistic Anisotropic Diffusion and Multi-scale Watersheds.- Error-Bounds on Curvature Estimation.- Multiresolution Approach to Biomedical Image Segmentation with Statistical Models of Appearance.- A Common Viewpoint on Broad Kernel Filtering and Nonlinear Diffusion.- Efficient and Consistent Recursive Filtering of Images with Reflective Extension.- Shape Description Using Gradient Vector Field Histograms.- Comparing Objective and Subjective Quality Results for Compression Pre-processing with Non-linear Diffusion.- Computation of Generic Features for Object Classification.- Gaussian Scale Space from Insufficient Image Information.- Families of Generalised Morphological Scale Spaces.- Detection and Localization of Random Signals.- Continuous Curve Matching with Scale-Space Curvature and Extrema-Based Scale Selection.