Geometric Computing

• Part I: Fundamentals of Geometric Algebra Introduction to Geometric Algebra Geometric Algebra for Modeling in Robot Physics Part II: Euclidean, Pseudo-Euclidean, Lie and Incidence Algebras and Conformal Geometries 2D, 3D and 4D Geometric Algebras Kinematics of the 2D and 3D Spaces Lie Algebras and Algebra of Incidence Using The Null Cone and Affine Plane Conformal Geometric Algebra Programming Issues Part III: Geometric Computing for Image Processing, Computer Vision and Neurocomputing Clifford Fourier and Wavelet Transforms Geometric Algebra of Computer Vision Geometric Neuralcomputing Part IV: Geometric Computing of Robot Kinematics and Dynamics Kinematics Dynamics Part V: Applications I: Image Processing, Computer Vision, Neurocomputing Applications of Lie Filters, Quaternion Fourier and Wavelet Transforms Invariants Theory in Computer Vision and Omnidirectional Vision Registration of 3D Points Using GA and Tensor Voting Applications in Neuralcomputing Neural Computing for 2D Contour and 3D Surface Reconstruction Part VI: Applications II: Robotics and Medical Robotics Rigid Motion Estimation Using Line Observations Tracker Endoscope Calibration and Body-Sensors Calibration Tracking, Grasping and Object Manipulation 3D Maps, Navigation and Relocalization Modeling and Registration of Medical Data Part VII: Appendix

From the reviews: "This book presents the theory and engineering applications of geometric algebra, a very powerful mathematical system. ... The results highlight that geometric algebra is a mathematical tool that can be used very advantageously in many engineering scenarios. ... has a real potential to convince a big audience of the benefits of using geometric algebra in engineering applications, and I hope that it will be successful." (Dietmar Hildenbrand, IAPR Newsletter, Vol. 33 (3), July, 2011) "The theory and applications of geometric algebra (Clifford algebra), an advanced mathematical language, are addressed in this book. ... The book is aimed at a graduate-level audience ... . it can also be well suited for teaching a course or for self-study at the postgraduate level. Each chapter is accompanied by numerous examples and figures ... . also be useful to scientists and engineers who are working in various areas related to the development and building of intelligent machines. I really enjoyed reading it." (George K. Adam, ACM Computing Reviews, October, 2010) "The subject of this interesting book is the application of geometric algebra to image processing, computer vision, neurocomputing and robotics. ... A notation table, a list of useful formulas, a bibliography and an index conclude the book. The book is well structured, rich in data, and it contains many exercises; it is aimed at graduate students." (Patrizio Frosini, Zentralblatt MATH, Vol. 1211, 2011)