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Scale Space Methods in Computer Vision

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Cover of 'Scale Space Methods in Computer Vision'

Table of Contents

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    Book Overview
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    Chapter 1 On Manifolds in Gaussian Scale Space
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    Chapter 2 Many-to-Many Matching of Scale-Space Feature Hierarchies Using Metric Embedding
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    Chapter 3 Content Based Image Retrieval Using Multiscale Top Points
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    Chapter 4 Feature Coding with a Statistically Independent Cortical Representation
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    Chapter 5 Scale-Space Image Analysis Based on Hermite Polynomials Theory
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    Chapter 6 A Complete System of Measurement Invariants for Abelian Lie Transformation Groups
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    Chapter 7 Equivalence Results for TV Diffusion and TV Regularisation
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    Chapter 8 Correspondences between Wavelet Shrinkage and Nonlinear Diffusion
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    Chapter 9 Approximating Non-linear Diffusion
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    Chapter 10 A Generalized Discrete Scale-Space Formulation for 2-D and 3-D Signals
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    Chapter 11 Real-Time Scale Selection in Hybrid Multi-scale Representations
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    Chapter 12 A Scale Space for Contour Registration Using Minimal Surfaces
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    Chapter 13 The Extrema Edges
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    Chapter 14 The Maximum Principle for Beltrami Color Flow
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    Chapter 15 The Monogenic Scale Space on a Bounded Domain and Its Applications
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    Chapter 16 Using the Complex Ginzburg-Landau Equation for Digital Inpainting in 2D and 3D
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    Chapter 17 Least Squares and Robust Estimation of Local Image Structure
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    Chapter 18 Regularity Classes for Locally Orderless Images
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    Chapter 19 Mode Estimation Using Pessimistic Scale Space Tracking
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    Chapter 20 Properties of Brownian Image Models in Scale-Space
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    Chapter 21 Image Decomposition Application to SAR Images
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    Chapter 22 Basic Morphological Operations, Band-Limited Images and Sampling
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    Chapter 23 An Explanation for the Logarithmic Connection between Linear and Morphological Systems
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    Chapter 24 Temporal Scale Spaces
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    Chapter 25 Temporal Structure Tree in Digital Linear Scale Space
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    Chapter 26 Interest Point Detection and Scale Selection in Space-Time
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    Chapter 27 Towards Recognition-Based Variational Segmentation Using Shape Priors and Dynamic Labeling
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    Chapter 28 PDE Based Shape from Specularities
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    Chapter 29 A Markov Random Field Approach to Multi-scale Shape Analysis
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    Chapter 30 Variational Dense Motion Estimation Using the Helmholtz Decomposition
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    Chapter 31 Regularizing a Set of Unstructured 3D Points from a Sequence of Stereo Images
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    Chapter 32 Image Reconstruction from Multiscale Critical Points
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    Chapter 33 Texture Classification through Multiscale Orientation Histogram Analysis
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    Chapter 34 α Scale Spaces on a Bounded Domain
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    Chapter 35 Efficient Beltrami Flow Using a Short Time Kernel
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    Chapter 36 Evolution of the Critical Points in the Curvature and Affine Morphological Scale Spaces
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    Chapter 37 MAPS: Multiscale Attention-Based PreSegmentation of Color Images
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    Chapter 38 Convex Colour Sieves
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    Chapter 39 Scale-Space on Image Profiles about an Object Boundary
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    Chapter 40 Iris Feature Extraction and Matching Based on Multiscale and Directional Image Representation
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    Chapter 41 Fast Computation of Scale Normalised Gaussian Receptive Fields
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    Chapter 42 A Multiphase Level Set Framework for Motion Segmentation
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    Chapter 43 Segmentation of Coarse and Fine Scale Features Using Multi-scale Diffusion and Mumford-Shah
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    Chapter 44 On the Number of Modes of a Gaussian Mixture
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    Chapter 45 Fully Automatic Segmentation of MRI Brain Images Using Probabilistic Anisotropic Diffusion and Multi-scale Watersheds
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    Chapter 46 Error-Bounds on Curvature Estimation
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    Chapter 47 Multiresolution Approach to Biomedical Image Segmentation with Statistical Models of Appearance
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    Chapter 48 A Common Viewpoint on Broad Kernel Filtering and Nonlinear Diffusion
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    Chapter 49 Efficient and Consistent Recursive Filtering of Images with Reflective Extension
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    Chapter 50 Shape Description Using Gradient Vector Field Histograms
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    Chapter 51 Scale Space Methods in Computer Vision
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    Chapter 52 Computation of Generic Features for Object Classification
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    Chapter 53 Gaussian Scale Space from Insufficient Image Information
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    Chapter 54 Families of Generalised Morphological Scale Spaces
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    Chapter 55 Detection and Localization of Random Signals
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    Chapter 56 Continuous Curve Matching with Scale-Space Curvature and Extrema-Based Scale Selection
Overall attention for this book and its chapters
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Title
Scale Space Methods in Computer Vision
Published by
Springer, Berlin, Heidelberg, January 2003
DOI 10.1007/3-540-44935-3
ISBNs
978-3-54-040368-5, 978-3-54-044935-5
Editors

Lewis D. Griffin, Martin Lillholm

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 9%
Unknown 10 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 9%
Unknown 10 91%
Readers by discipline Count As %
Computer Science 1 9%
Unknown 10 91%