A Sampler of Useful Computational Tools for Applied - download pdf or read online

By Daniel Cohen-Or, Chen Greif, Tao Ju, Niloy J. Mitra, Ariel Shamir, Olga Sorkine-Hornung, Hao (Richard) Zhang

ISBN-10: 1498706304

ISBN-13: 9781498706308

A Sampler of helpful Computational instruments for utilized Geometry, special effects, and photograph Processing exhibits find out how to use a set of mathematical suggestions to resolve vital difficulties in utilized arithmetic and laptop technological know-how components. The publication discusses primary instruments in analytical geometry and linear algebra. It covers quite a lot of themes, from matrix decomposition to curvature research and valuable part research to dimensionality reduction.

Written by means of a staff of hugely revered professors, the ebook can be utilized in a one-semester, intermediate-level path in computing device technology. It takes a pragmatic problem-solving procedure, averting specified proofs and research. appropriate for readers and not using a deep educational history in arithmetic, the textual content explains how you can clear up non-trivial geometric difficulties. It speedy will get readers in control on numerous instruments hired in visible computing and utilized geometry.

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Extra resources for A Sampler of Useful Computational Tools for Applied Geometry, Computer Graphics, and Image Processing

Sample text

Xi )/∂a)[yi − fabc... (xi )] = 0, ∂E(a, b, c, . . )/∂a = i (−2∂fabc... (xi )/∂b)[yi − fabc... (xi )] = 0, ∂E(a, b, c, . . )/∂b = i .. 9) Since we assumed that f (x) linearly depends on the parameters, terms like ∂f (xi )/∂a, ∂f (xi )/∂b, . . work out such that the above system of equations is still linear in the parameters a, b, . . ,λk (x) = λ1 f1 (x) + λ2 f2 (x) + · · · + λk fk (x) . 38 Least-Squares Solutions Solving linear systems in the LS sense Often in linear algebra we have to solve a set of m linear equations involving n unknowns.

We compute the LS line fit to a set of weighted points. At the beginning all points are considered equal, but as we know more about the points and their relation to the underlying model, we can progressively identify and down-weigh the outliers. Let points pi have weights wi ∈ [0, 1], then our new optimization becomes n wi d(l, pi )2 . 12) i=1 Using the vertical distance formulation, the new linear system formulation for fitting a straight line in the LS sense reduces to i wi x2i wi xi wi xi wi a b = i wi x i yi wi yi .

The norm of a vector u is a scalar denoted by u , which satisfies the following properties: • u ≥ 0, and u = 0 if and only if u = 0, namely all of the components of u are zero. • For any scalar α and a vector u, αu = |α| · u . • The triangle inequality holds: u + v ≤ u + v for any two vectors u and v. Notice that for numbers, namely vectors of length one, the absolute value is trivially a valid norm that satisfies the above three properties. For vectors, lp -norms are commonly used and are defined as n u p 1/p |ui |p = .

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A Sampler of Useful Computational Tools for Applied Geometry, Computer Graphics, and Image Processing by Daniel Cohen-Or, Chen Greif, Tao Ju, Niloy J. Mitra, Ariel Shamir, Olga Sorkine-Hornung, Hao (Richard) Zhang


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