Geometry of Shape Manifolds - PowerPoint PPT Presentation

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Geometry of Shape Manifolds

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Move along manifold by moving in tangent space and projecting back to manifold ... Approximate f with its first m 1 cosine components and its first m sine components: ... – PowerPoint PPT presentation

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Title: Geometry of Shape Manifolds


1
Geometry of Shape Manifolds
  • Constraints define a manifold embedded in q0 L2
  • Move along manifold by moving in tangent space
    and projecting back to manifold
  • Tangent space is infinite dimensional, but normal
    space is characterized by three constraints
    defined in f1

2
Tangents and Normals
  • The derivative of f1 in the direction of f at ?
    is
  • Implies df1 is surjective
  • If f is orthogonal to 1, sin q, cos q, then
    df10 in the direction of f and hence f is in the
    tangent space

3
Projections
  • Want to find the closest element in C1 to an
    arbitrary q ? q0 L2
  • Basic idea move orthogonal to level sets so
    projections under f form a straight line in R3
  • For a point b ? R3, we define the level set as
  • Let b1(p,0,0). Then its level set is the
    preshape space C1

4
Approximate Projections
  • If points are close to C1, then one can use a
    faster method
  • Let dq be the normal vector at q for which
    f(qdq)b1. Can do first order approximation to
    compute this
  • Approximate Jacobian as

5
Iterative algorithm
  • Define the residual (error) vector as
  • Then
  • where
  • Iteratively update q dq? q until the error goes
    to zero
  • Call this projection operator P

6
Example Projections
Fig. 1 Projections of arbitrary curves into C1
7
Geodesics
  • Definition For a manifold embedded in Euclidean
    space, a geodesic is a constant speed curve whose
    acceleration vector is always perpendicular to
    the manifold
  • Define the metric between two shapes as the
    distance along the manifold between the shapes
    with respect to the L2 inner product
  • Nice features
  • Defined for all closed curves
  • Interpolants are closed curves
  • Finds geodesics in a local sense, not necessarily
    global

8
Paths from initial conditions
  • Assume we have a q in C1 and an f in the tangent
    space
  • Approximate geodesic along manifold by moving to
    qfDt and projecting that back onto the manifold
    (Dt is step size)
  • So q(tDt) P(q(t)f(t)Dt)

9
Transporting the tangent vector
  • Now f(t) is not in the tangent space of q(tDt)
  • Two conditions for a geodesic
  • The acceleration vector must be perpendicular to
    the manifold simply project f into the next
    tangent space
  • The curve must move at constant speed
    renormalize so f(t1)f(t)
  • hk is the orthonormal basis of the normal space

10
Geodesics on shape spaces
  • S1 is a quotient space of C1 under actions of S1
    by isometries, so finding geodesics in S1
    equivalent to finding geodesics in C1 which are
    orthogonal to S1 orbits
  • S1 acting by isometries implies that if a
    geodesic in preshape space is orthogonal to one
    S1 orbit, its orthogonal to all S1 orbits which
    it meets
  • So now normal space has one additional component
    spanned by
  • The algorithm is the same as detailed earlier
    except with an expanded normal space

11
Geodesics between shapes
  • We know how to generate geodesic paths given q
    and f
  • Now we want to construct a geodesic path from q1
    to q2
  • So we need to find all f that lead from q1 to an
    S1 orbit of q2 in unit time, and then choose the
    one that leads to the shortest path
  • Let Y define the geodesic flow, with ?(q1,0,f)q1
    as the initial condition
  • We then want Y(q1,1,f)q2

12
Finding the geodesic
  • Define an error functional which measures how
    close we are to the target at t1
  • Choose the geodesic as the flow Y which has the
    smallest initial velocity f
  • i.e., min f s.t. Hf0
  • Hard because infinite dimensional search

13
Fourier decomposition
  • f ? L2, so it has a Fourier decomposition
  • Approximate f with its first m1 cosine
    components and its first m sine components
  • Let a be the vector containing all of the Fourier
    coefficients
  • Now optimization problem is min a s.t. Ha0

14
Geodesic paths
Fig. 2 Geodesic paths between two shapes
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