Conformal geometric algebra
Conformal geometric algebra is the geometric algebra constructed over the resultant space of a map from points in an -dimensional base space to null vectors in. This allows operations on the base space, including reflections, rotations and translations to be represented using versors of the geometric algebra; and it is found that points, lines, planes, circles and spheres gain particularly natural and computationally amenable representations.
The effect of the mapping is that generalized -spheres in the base space map onto -blades, and so that the effect of a translation of the base space corresponds to a rotation in the higher-dimensional space. In the algebra of this space, based on the geometric product of vectors, such transformations correspond to the algebra's characteristic sandwich operations, similar to the use of quaternions for spatial rotation in 3D, which combine very efficiently. A consequence of rotors representing transformations is that the representations of spheres, planes, circles and other geometrical objects, and equations connecting them, all transform covariantly. A geometric object can be synthesized as the wedge product of linearly independent vectors representing points on the object; conversely, the object can be decomposed as the repeated wedge product of vectors representing distinct points in its surface. Some intersection operations also acquire a tidy algebraic form: for example, for the Euclidean base space, applying the wedge product to the dual of the tetravectors representing two spheres produces the dual of the trivector representation of their circle of intersection.
As this algebraic structure lends itself directly to effective computation, it facilitates exploration of the classical methods of projective geometry and inversive geometry in a concrete, easy-to-manipulate setting. It has also been used as an efficient structure to represent and facilitate calculations in screw theory. CGA has particularly been applied in connection with the projective mapping of the everyday Euclidean space into a five-dimensional vector space, which has been investigated for applications in robotics and computer vision. It can be applied generally to any pseudo-Euclidean space, and the mapping of Minkowski space to the space is being investigated for applications to relativistic physics.
Construction of CGA
Notation and terminology
In this article, the focus is on the algebra as it is this particular algebra that has been the subject of most attention over time; other cases are briefly covered in a separate section.The space containing the objects being modelled is referred to here as the base space, and the algebraic space used to model these objects as the representation or conformal space. A homogeneous subspace refers to a linear subspace of the algebraic space.
The terms for objects: point, line, circle, sphere, quasi-sphere etc. are used to mean either the geometric object in the base space, or the homogeneous subspace of the representation space that represents that object, with the latter generally being intended unless indicated otherwise. Algebraically, any nonzero null element of the homogeneous subspace will be used, with one element being referred to as normalized by some criterion.
Boldface lowercase Latin letters are used to represent position vectors from the origin to a point in the base space. Italic symbols are used for other elements of the representation space.
Base and representation spaces
The base space is represented by extending a basis for the displacements from a chosen origin and adding two basis vectors and orthogonal to the base space and to each other, with and, creating the representation space.It is convenient to use two null vectors and as basis vectors in place of and, where, and .
It can be verified, where is in the base space, that:
These properties lead to the following formulas for the basis vector coefficients of a general vector in the representation space for a basis with elements orthogonal to every other basis element:
Mapping between the base space and the representation space
The mapping from a vector in the base space is given by the formula:Points and other objects that differ only by a nonzero scalar factor all map to the same object in the base space. When normalisation is desired, as for generating a simple reverse map of a point from the representation space to the base space or determining distances, the condition may be used.
The forward mapping is equivalent to:
- first conformally projecting from onto a unit 3-sphere in the space ;
- then lift this into a projective space, by adjoining, and identifying all points on the same ray from the origin ;
- then change the normalisation, so the plane for the homogeneous projection is given by the co-ordinate having a value, i.e..
Inverse mapping
This first gives a stereographic projection from the light-cone onto the plane, and then throws away the and parts, so that the overall result is to map all of the equivalent points to.
Origin and point at infinity
The point in maps to in, so is identified as the vector of the point at the origin.A vector in with a nonzero coefficient, but a zero coefficient, must be the image of an infinite vector in. The direction therefore represents the point at infinity. This motivates the subscripts and for identifying the null basis vectors.
The choice of the origin is arbitrary: any other point may be chosen, as the representation is of an affine space. The origin merely represents a reference point, and is algebraically equivalent to any other point. As with any translation, changing the origin corresponds to a rotation in the representation space.
Geometrical objects
Basis
Together with and, these are the 32 basis blades of the algebra.The Flat Point Origin is written as an outer product because the geometric product is of mixed grade..
Elements | Geometric Concept |
Point and Dual Sphere | |
Without is Dual Plane | |
Point Pair | |
Bivector | |
Tangent vector | |
Direction vector | |
Flat Point Origin * | |
Circle | |
3D Pseudoscalar | |
Tangent Bivector | |
Direction Bivector | |
Sphere | |
Without is the Plane | |
As the solution of a pair of equations
Given any nonzero blade of the representing space, the set of vectors that are solutions to a pair of homogeneous equations of the formis the union of homogeneous 1-d subspaces of null vectors, and is thus a representation of a set of points in the base space. This leads to the choice of a blade as being a useful way to represent a particular class of geometric object. Specific cases for the blade when the base space is Euclidean space are:
- a scalar: the empty set
- a vector: a single point
- a bivector: a pair of points
- a trivector: a generalized circle
- a 4-vector: a generalized sphere
- etc.
The listed geometric objects become quasi-spheres in the more general case of the base space being pseudo-Euclidean.
Flat objects may be identified by the point at infinity being included in the solutions. Thus, if, the object will be a line, plane, etc., for the blade respectively being of grade 3, 4, etc.
As derived from points of the object
A blade representing of one of this class of object may be found as the outer product of linearly independent vectors representing points on the object. In the base space, this linear independence manifests as each point lying outside the object defined by the other points. So, for example, a fourth point lying on the generalized circle defined by three distinct points cannot be used as a fourth point to define a sphere.odds
compare:- x. a = 0 => x perp a; x. = 0 => x perp a and x perp b
- x∧a = 0 => x parallel to a; x∧ = 0 => x parallel to a or to b
g(x) . A = 0
Transformations
This reflection operation can be used to build up general translations and rotations:Generalizations
History
Books
- Hestenes et al, in G. Sommer, Geometric Computing with Clifford Algebra. Springer Verlag.
- * Ch. 1:
- * Ch. 2:
- * Ch. 3:
- * Ch. 4:
- Hestenes, in E. Bayro-Corrochano & G. Sobczyk, Advances in Geometric Algebra with Applications in Science and Engineering, Springer Verlag.
- *
- Hestenes, in E. Bayro-Corrochano and G. Scheuermann, Geometric Algebra Computing in Engineering and Computer Science. Springer Verlag. .
- *
- Doran, C. and Lasenby, A., Geometric algebra for physicists, Cambridge University Press. §10.2; p. 351 et seq
- Dorst, L. et al, Geometric Algebra for Computer Science, Morgan-Kaufmann. Chapter 13; p. 355 et seq
- Vince, J., Geometric Algebra for Computer Graphics, Springer Verlag. Chapter 11; p. 199 et seq
- Perwass, C., Geometric Algebra with Applications in Engineering, Springer Verlag. §4.3: p. 145 et seq
- Bayro-Corrochano, E. and Scheuermann G., Geometric Algebra Computing in Engineering and Computer Science. Springer Verlag. pp. 3–90
- Bayro-Corrochano, Geometric Computing for Wavelet Transforms, Robot Vision, Learning, Control and Action. Springer Verlag. Chapter 6; pp. 149–183
- Dorst, L. and Lasenby, J., Guide to Geometric Algebra in Practice. Springer Verlag, pp. 3–252..
Online resources
- Wareham, R., ', PhD thesis, University of Cambridge, pp. 14–26, 31—67
- Bromborsky, A.,
- Dell’Acqua, A. et al, , Image and Vision Computing, 26' 529–549
- Dorst, L., , in E. Bayro-Corrochano, G. Scheuermann, Geometric Algebra Computing, Springer Verlag.
- Colapinto, P., , MSc thesis, University of California Santa Barbara
- Macdonald, A., . §4.2: p. 26 et seq.
- on the motor algebra over ℝn+1:
- * Eduardo Bayro Corrochano, Geometric computing for perception action systems: Concepts, algorithms and scientific applications''.