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

€105.99
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Age Group_Uncategorized
analytical geometry
automatic-update
B01=Ariel Shamir
B01=Chen Greif
B01=Daniel Cohen-Or
B01=Hao (Richard) Zhang
B01=Niloy J. Mitra
B01=Olga Sorkine-Hornung
B01=Tao Ju
Category1=Non-Fiction
Category=PBM
Category=PBW
Category=UG
Category=UYT
Contour Vertices
COP=United States
curvature analysis
Data Set
Delivery_Pre-order
digital geometry processing
dimensionality reduction
Discrete Laplacian Operator
Discrete Sine Transform
dynamic programming
eq_bestseller
eq_computing
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Gaussian Elimination
geometric algorithms
image manipulation
Incomplete LU Factorization
intermediate computer science
Kernel PCA
Krylov Subspace
Language_English
Laplacian Smoothing
Latin Square
linear algebra
LS Solution
LU Decomposition
mathematical modelling
matrix decomposition
matrix factorisation
Monge Patch
non-trivial geometric problems
numerical methods
PA=Temporarily unavailable
Piecewise Linear Interpolation
practical problem solving in geometry
Price_€50 to €100
principal component analysis
Principal Curvatures
PS=Active
Scatter Matrix
scientific visualisation
Shepard's Interpolation
Shepard’s Interpolation
Skewing Schemes
softlaunch
SPD
Spectral Coefficients
Spectral Embedding
Spectral Transform
Triangle Mesh
Vertical Seam
Vice Versa
visual computing

Product details

  • ISBN 9781498706285
  • Weight: 628g
  • Dimensions: 178 x 254mm
  • Publication Date: 21 May 2015
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
  • Language: English
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Description

A Sampler of Useful Computational Tools for Applied Geometry, Computer Graphics, and Image Processing shows how to use a collection of mathematical techniques to solve important problems in applied mathematics and computer science areas. The book discusses fundamental tools in analytical geometry and linear algebra. It covers a wide range of topics, from matrix decomposition to curvature analysis and principal component analysis to dimensionality reduction.

Written by a team of highly respected professors, the book can be used in a one-semester, intermediate-level course in computer science. It takes a practical problem-solving approach, avoiding detailed proofs and analysis. Suitable for readers without a deep academic background in mathematics, the text explains how to solve non-trivial geometric problems. It quickly gets readers up to speed on a variety of tools employed in visual computing and applied geometry.

About

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