Geometric Properties for Incomplete Data

From the reviews: "This compendium should be treated as a higher-level text with the target audience being computer scientists, electrical engineers, and mathematician, both in the research and industrial settings. Graduate-level students interested in pursuing advanced treatments of the topic can benefit from reading this book as well. ... This text is an important and worthwhile contribution to the computational imaging and vision literature; it is easy to read and rigorous in its mathematical development." (R. Goldberg, ACM Computing Reviews, Vol. 49 (4), April, 2008)

• Contributors. Preface. I Continuous Geometry: Representation of Free-form Objects. Spheres and Conics. Algorithms for Spatial Pythagoreanhodograph Curves. Cumulative Chords, Piecewise-Quadratics and Piecewise-Cubics. Spherical Splines. Graph-Spectral Methods for Surface Height Recovery from Gauss Maps.- II Discrete Geometry: Segmentation of Boundaries into Convex and Concave Parts. Convex and Concave Parts of Digital Curves. Polygonalisation and Polyhedralisation by Optimisation. Binary Tomography by Iterating Linear Programs. Cascade of dual LDA Operators for Face Recognition. Precision of Geometric Moments in Picture Analysis. Shape-from-Shading by Iterative Fast Marching for Vertical and Oblique Light Sources. Shape from Shadows.- III Approximation and Regularization: A Confidence Measure for Variational Optic Flow Methods. Video Image Sequence Analysis: Estimating Missing Data and Segmenting Multiple Motions. Robust Local Approximation of Scattered Data. On Robust Estimation and Smoothing with Spatial and Tonal Kernels. Subspace Estimation with Uncertain and Correlated Data. On the use of Dual Norms in Bounded Variation Type Regularization.- Index.