Innovations for Shape Analysis: Models and Algorithms

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Part I Discrete Shape Analysis
	Chapter
1 Modeling Three-Dimensional Morse and Morse-SmaleComplexes
	Chapter
2 Geodesic Regression and Its Application to Shape Analysis
	Chapter
3 Segmentation and Skeletonization on Arbitrary Graphs Using Multiscale Morphology and Active Contours
	Chapter
4 Refined Homotopic Thinning Algorithms and Quality Measures for Skeletonisation Methods
	Chapter
5 Nested Sphere Statistics of Skeletal Models
	Chapter
6 3D Curve Skeleton Computation and Use for Discrete Shape Analysis
	Chapter
7 Orientation and Anisotropy of Multi-component Shapes
Part II Partial Differential Equations for Shape Analysis
	Chapter
8 Stable Semi-local Features for Non-rigid Shapes
	Chapter
9 A Brief Survey on Semi-Lagrangian Schemesfor Image Processing
	Chapter
10 Shape Reconstruction of Symmetric Surfaces Using Photometric Stereo
	Chapter
11 Remeshing by Curvature Driven Diffusion
	Chapter
12 Group-Valued Regularization for Motion Segmentation of Articulated Shapes
	Chapter
13 Point Cloud Segmentation and Denoising via Constrained Nonlinear Least Squares Normal Estimates
	Chapter
14 Distance Images and the Enclosure Field: Applications in Intermediate-Level Computer and Biological Vision
Part III Optimization Methods for Shape Analysis
	Chapter
15 Non-rigid Shape Correspondence Using Pointwise Surface Descriptors and Metric Structures
	Chapter
16 A Review of Geometry Recovery from a Single Image Focusing on Curved Object Reconstruction
	Chapter
17 On Globally Optimal Local Modeling: From Moving Least Squares to Over-parametrization
	Chapter
18 Incremental Level Set Tracking
	Chapter
19 Simultaneous Convex Optimization of Regions and Region Parameters in Image Segmentation Models
	Chapter
20 Fluctuating Distance Fields, Parts, Three-Partite Skeletons
	Chapter
21 Integrated DEM Construction and Calibration of Hyperspectral Imagery: A Remote Sensing Perspective
Index