FFTs in Graphics and Vision. Rotational and Reflective Symmetry Detection

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FFTs in Graphics and Vision Rotational and Reflective Symmetry Detection

Outline Representation Theory Symmetry Detection Rotational Symmetry Reflective Symmetry

Representation Theory Recall: A group is a set of elements G with a binary operation (often denoted ) such that for allf, g, h G, the following properties are satisfied: Closure: g h G Associativity: f g h = f g h Identity: There exists an identity element 1 G s.t.: 1 g = g 1 = g Inverse: Every element g has an inverse g 1 s.t.: g g 1 = g 1 g = 1

Representation Theory Observation 1: Given a group G = {g 1,, g n }, for any g G, the (set-theoretic) map that multiplies the elements of G on the left by g is invertible. (The inverse is the map multiplying the elements of G on the left by g 1.)

Representation Theory Observation 1: In particular, the set {g g 1,, g g n } is just a reordering of the set {g 1,, g n }. Or more simply, g G = G. Similarly, the set {g 1 1,, g n 1 } is just a reordering of the set {g 1,, g n }. Or more simply, G 1 = G.

Representation Theory Recall: A Hermitian inner product is a map from V V into the complex numbers that is: 1. Linear: For all u, v, w V and any scalar λ C u + v, w = u, w + v, w λv, w = λ v, w 2. Conjugate Symmetric: For all v, w V v, w = w, v 3. Positive Definite: For all v V v, v 0 v, v = 0 v = 0

Representation Theory Observation 2: Given a Hermitian inner-product space V, and vectors v 1,, v n V, the vector minimizing the sum of squared distances is the average: 1 n n k=1 v k = arg min v V n k=1 v v k 2

Representation Theory Recall: A unitary representation of a group G on a Hermitian inner-product space V is a map ρ that sends every element in G to an orthogonal transformation on V, satisfying: ρ g h = ρ g ρ h for all g, h G.

Representation Theory Definition: A vector v V is invariant under the action of G if: ρ g v = v for all g G. We denote by V G the set of vectors in V that are invariant under the action of G: V G = v V ρ g v = v, g G

Representation Theory Observation 3: The set V G is a vector sub-space of V. If v, w V G, then for any g G, we have: ρ g v = v and ρ g w = w And for all scalars α and β we have: ρ g α v + β w = α ρ g v + β ρ g w = α v + β w So α v + β w V G as well.

Representation Theory Observation 4: Given a finite group G and given a vector v V, the average of v over G: Average v, G = 1 G g G ρ g (v) is invariant under the action of G.

Representation Theory Observation 4: Let h be any element in G. We would like to show that h maps the average back to itself: Average v, G = ρ h Average v, G

Representation Theory Observation 4: Average v, G = ρ h Average v, G = ρ h 1 G g G ρ g v = 1 G g G ρ h ρ g v = 1 G g G ρ h g v = 1 G g h G ρ g v = 1 G g G ρ g v = Average(v, G)

Representation Theory Observation 5: Given a finite group G and given a vector v V, the average of v over G is the closest G-invariant vector to v: Average v, G = arg min v 0 V G ( v 0 v 2 )

Representation Theory Observation 5: v 0 v 2 = 1 G g G ρ g v 0 v 2 = 1 G g G v 0 ρ g 1 (v) 2 = 1 G g G v 0 ρ g 1 (v) 2 = 1 G g G 1 v 0 ρ g (v) 2 = 1 G g G v 0 ρ g (v) 2

Representation Theory Observation 5: v 0 v 2 = 1 G g G v 0 ρ g (v) 2 Thus, v 0 is the G-invariant vector minimizing the squared distance to v if and only if it minimizes the sum of squared distances to the vectors: ρ g1 v,, ρ gn v So v 0 must be the average of these vectors: v 0 = 1 G g G ρ g (v) = Average(v, G)

Representation Theory Note: Since the average map: Average v, G = 1 G = g G ρ g (v) is a linear map returning the closest G-invariant vector to v, it is the projection map from V to V G.

Outline Representation Theory Symmetry Detection Rotational Symmetry Reflective Symmetry

Symmetry Detection For functions on a circle, we defined measures of: Reflective Symmetry: for every axis of reflective symmetry. Rotational Symmetry: for every order of rotational symmetry. 120 45 Reflective 3-Fold Rotational 8-Fold Rotational

Symmetry Detection For functions on a sphere, we would like to define a measure of: Reflective Symmetry: for every plane of reflective symmetry.

Symmetry Detection For functions on a sphere, we would like to define a measure of: Reflective Symmetry: for every plane of reflective symmetry. Rotational Symmetry: for every axis through the origin and every order of rotational symmetry.

Symmetry Detection Goal: Reflective Symmetry: Compute the spherical function giving the measure of reflective symmetry of every plane passing through the origin. Rotational Symmetry: For every order of rotational symmetry k:» Compute the spherical function giving the measure of k-fold symmetry about every axis through the origin.

Symmetry Detection Goal: Reflective Symmetries 2-Fold Rotational Symmetries Model 3-Fold Rotational Symmetries 4-Fold Rotational Symmetries

Symmetry Detection Approach: As in the 1D case, we will compute the symmetries of a shape by representing the shape by a spherical function. Model Spherical Extent Function

Symmetry Detection Recall: To measure a function s symmetry we: Associated a group G of transformations to each type of symmetry Defined the measure of symmetry as the size of the closest G-invariant function: Sym 2 f, G = π G f 2 Since the nearest symmetric function is the average under the action of the group, we got: Sym 2 f, G = 1 2 ρ G g f g G

Outline Representation Theory Symmetry Detection Rotational Symmetry Reflective Symmetry

Rotational Symmetry Given a function on the sphere, and given a fixed order of rotational symmetry k, define a function whose value at a point is the measure of k-fold rotational symmetry about the associated axis. k = 2 k = 3 k = 5

Rotational Symmetry To do this, we need to associate a group to every axis passing through the origin. We denote by G p,k the group of k-fold rotations about the axis through p. The elements of the group are the rotations: g j = R p, 2jπ k corresponding to rotations about p by the angle 2jπ/k. x z 2/k p y

Rotational Symmetry k 1 Sym 2 f, G p,k = 1 k j=0 ρ gj f 2 k 1 k 1 = 1 k 2 ρ gi (f), i=0 k 1 j=0 ρ gj (f) = 1 k 2 ρ gi (f), ρ gj (f) i,j=0 k 1 = 1 k 2 f, ρ gj i (f) i,j=0 k 1 = 1 f, ρ k gj (f) j=0

Rotational Symmetry Sym 2 f, G p,k k 1 = 1 k j=0 f, ρ gj (f) The measure of k-fold rotational symmetry about the axis p can be computed by taking the average of the dot-products of the function f with its k rotations about the axis p.

Rotational Symmetry Sym 2 f, G p,k k 1 = 1 k j=0 f, ρ gj (f) So computing the measures of rotational symmetry reduces to the problem of computing the correlation of f with itself: Dot f,f R = f, ρ R f And this is something that we can do using the Wigner D-transform from last lecture.

Rotational Symmetry Sym 2 f, G p,k k 1 = 1 k j=0 f, ρ gj (f) Algorithm: Given a function f: Compute the auto-correlation of f. For each order of symmetry k:» Compute the spherical function whose value at p is the average of the correlation values at rotations R p, 2πj, with 0 j < k. k

Rotational Symmetry Sym 2 f, G p,k k 1 = 1 k j=0 f, ρ gj (f) Complexity: Compute the auto-correlation: O(n 3 log 2 n) For each order of symmetry k: Compute the spherical function: O(n 2 k) Giving a complexity of O(n 2 k 2 + n 3 log 2 n) to compute all rotational symmetries.

Outline Representation Theory Symmetry Detection Rotational Symmetry Reflective Symmetry

Reflective Symmetry Given a spherical function f, we would like to compute a function whose value at a point p is the measure of reflective symmetry with respect to the plane perpendicular to p. p

Reflective Symmetry Reflections through the plane perpendicular to p correspond to a group with two elements: G p = Id, Ref p p

Reflective Symmetry Reflections through the plane perpendicular to p correspond to a group with two elements: G p = Id, Ref p So the measure of reflective symmetry becomes: Sym 2 f, G p = 1 2 f, f + f, ρ Ref p f = 1 2 f 2 + f, ρ Refp f

Reflective Symmetry How do we compute the dot-product of the function f with the reflection of f through the plane perpendicular to p? Since reflections are not rotations we cannot use the auto-correlation (directly).

Reflective Symmetry General Approach: If we have two reflections S and T, we can set R to be the transformation: R = T S Since S and T are both orthogonal, the product R must also be orthogonal. Since both S and T have determinant 1, R must have determinant 1.

Reflective Symmetry General Approach: If we have two reflections S and T, we can set R to be the transformation: R = T S Thus, R must be a rotation and we have: T = R S 1 = R S Any reflection T can be expressed as the product of a fixed reflection S with some rotation.

Reflective Symmetry General Approach: If we compute the correlation of f with some reflection ρ S (f): Dot f,ρs f (R) = f, ρ R ρ s f Then we can get the dot-product of f with its reflection through the plane perpendicular to p: f, ρ Refp f = f, ρ Refp S ρ s f = Dot f,ρs f (Ref p S) Rotation

Reflective Symmetry Sym 2 f, G p = 1 2 f 2 + Dot f,ρs f Ref p S Algorithm: Given a function f: Compute the correlation of f with ρ S (f) Compute the spherical function whose value at p is the average of the size of f and the dot-product of f with the rotation of ρ S (f) by Ref p S.

Reflective Symmetry Sym 2 f, G p = 1 2 f 2 + Dot f,ρs f Ref p S Complexity: Compute the correlation: O n 3 log 2 n Compute the spherical function: O(n 2 ) Giving a complexity of O(n 3 log 2 n) to compute all reflective symmetries.

Reflective Symmetry Sym 2 f, G p = 1 2 f 2 + Dot f,ρs f Ref p S Complexity: Compute the correlation: O n 3 log 2 n For computing reflective symmetries, the computation of the correlation is overkill as we don t use most of the correlation values. Compute the spherical function: O(n 2 ) Giving a complexity of O(n 3 log 2 n) to compute all reflective symmetries.

Reflective Symmetry There are many different choices for the reflection S we use to compute: Dot f,ρs f (R) A simple reflection is the antipodal map: 1 0 0 S = 0 1 0 0 0 1

Reflective Symmetry The advantage of using the antipodal map is that it makes it easy to express Ref p S. Fixing a point p, S is the composition of two maps: A reflection through the plane perpendicular to p, and A rotation by 180 about the axis through p. p

Reflective Symmetry So a reflection through the plane perpendicular to p is the product of the antipodal map and a rotation by 180 around the axis through p: Ref p = R p, π S p

Reflective Symmetry Setting S to be the antipodal map, we get: Sym 2 f, G p = 1 2 f 2 + f, ρ R p,π ρ S f Note that evaluating reflective symmetry only requires knowing the correlation values for 180 rotations.

Reflective Symmetry Since the spherical harmonics of degree l are homogenous polynomials of degree l, we get a simple expression for ρ S (f): ρ S f = l 1 l l m= l f l, m Y l m

Reflective Symmetry Y (, 0 0 ) Im Y 1 (, 1 ) Y (, 0 1 ) Re Y 1 (, 1 ) Im Y 2 2 (, ) Im Y 1 2 (, ) Y (, 0 2 ) Re Y 1 2 (, ) Re Y (, 2 2 ) Im Y 3 (, 3 ) Im Y 3 (, 2 ) Im Y 1 (, 3 ) 0 Y3 (, ) 2 Y, ) ReY (, ) Re 1 ( 3 3 Re Y 3 (, 3 )

Reflective Symmetry In particular, if f is antipodally symmetric: ρ S f = f we have: Sym 2 f, G p = 1 2 = 1 2 f 2 + f, ρ R p,π f 2 + f, ρ R p,π ρ S f f = Sym 2 f, G p,2

Reflective Symmetry That is, if f is antipodally symmetric, the 2-fold rotational symmetries of f and the reflective symmetries of f are the same. 2-Fold Symmetry Benzene Reflective Symmetry