SlideShare uma empresa Scribd logo
1 de 29
Baixar para ler offline
Problem
                                     Our approach
                                          Example
                                      Future work




          Closed formulae for distance functions
                    involving ellipses.

    F. Etayo1 , L. Gonzalez-Vega1 , G. R. Quintana1 , W. Wang2

                1 Departamento      de Matemáticas, Estadística y Computación
                                     Universidad de Cantabria
                               2 Department   of Computer Science
                                      University of Hong Kong


      VII International Workshop on Automated Deduction in
                            Geometry

F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang   ADG 2008
Problem
                                       Our approach
                                            Example
                                        Future work


Contents


  1   Problem

  2   Our approach

  3   Example

  4   Future work




  F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang   ADG 2008
Problem
                                       Our approach
                                            Example
                                        Future work


Introduction

  We want to compute the distance between two coplanar
  ellipses.


  The minimum distance between a given point and one ellipse is
  a positive algebraic number: our goal is to determine a
  polynomial with this number as a real root.


  This way of presenting the distance is independent of the
  corresponding footpoints and provides the distance directly. We
  can use this formula for analyzing the Ellipses Moving Problem
  (EMP).


  F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang   ADG 2008
Problem
                                       Our approach
                                            Example
                                        Future work


Applications

  The computation of the minimum distance between two ellipses
  (static or dynamic) is a fundamental task in various
  applications:
        collision detection in robotics,
        interference avoidance in CAD/CAM,
        interactions in virtual reality,
        computer games,
        orbit analysis (non-coplanar ellipses),
        interference analysis of molecules in computational
        physics and chemistry,
        etc.

  F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang   ADG 2008
Problem
                                       Our approach
                                            Example
                                        Future work


Previous works


        I. Z. E MIRIS , E. T SIGARIDAS , G. M. T ZOUMAS . The
        predicates for the Voronoi diagram of ellipses. Proc. ACM
        Symp. Comput. Geom., 2006.
        I. Z. E MIRIS , G. M. T ZOUMAS . A Real-time and Exact
        Implementation of the predicates for the Voronoi Diagram
        for parametric ellipses. Proc. ACM Symp. Solid Physical
        Modelling, 2007.
        C. L ENNERZ , E. S CHÖMER . Efficient Distance
        Computation for Quadratic Curves and Surfaces.
        Geometric Modelling and Processing Proceedings, 2002.



  F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang   ADG 2008
Problem
                                       Our approach
                                            Example
                                        Future work


Previous works


        J.-K. S EONG , D. E. J OHNSON , E. C OHEN . A Higher
        Dimensional Formulation for Robust and Interactive
        Distance Queries. Proc. ACM Solid and Physical
        Modeling, 2006.
        K.A. S OHN , B. J ÜTTLER , M.S. K IM , W. WANG .
        Computing the Distance Between Two Surfaces via Line
        Geometry. Proc. Tenth Pacific Conference on Computer
        Graphics and Applications, 236-245, IEEE Press, 2002.
  Common aspect: the problem is always solved by determining,
  first, the footpoints and then the searched distance.


  F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang   ADG 2008
Problem
                                       Our approach
                                            Example
                                        Future work


Our approach



  We do not make the minimum distance computation depending
  on the determination of the footpoints. We study the ellipse
  separation problem by analyzing the univariate polynomial
  providing the distance.


  Parameters of our problem: center coordinates, axes length,
  inclination of the axes.




  F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang   ADG 2008
Problem
                                       Our approach
                                            Example
                                        Future work


Our approach


  We do not make the minimum distance computation depending
  on the determination of the footpoints. We study the ellipse
  separation problem by analyzing the univariate polynomial
  providing the distance.


  Parameters of our problem: center coordinates, axes length,
  inclination of the axes.
  Is there any advantage?




  F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang   ADG 2008
Problem
                                       Our approach
                                            Example
                                        Future work


Our approach

  We do not make the minimum distance computation depending
  on the determination of the footpoints. We study the ellipse
  separation problem by analyzing the univariate polynomial
  providing the distance.


  Parameters of our problem: center coordinates, axes length,
  inclination of the axes.
  Is there any advantage?


  Indeed: the distance behaves continuously but footpoints do
  not.


  F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang   ADG 2008
Problem
                                        Our approach
                                             Example
                                         Future work


The distance of a point to an ellipse


  We consider the parametric equations of an ellipse, ε0 :
                  √            √
              x = a cos t, y = b sin t, t ∈ [0, 2π)

  in order to construct a function fd whose minimum positive
  value, d, gives the square of the distance between a point
  (x0 , y0 ) and the ellipse:
                            √               √
               fd := (x0 − a cos t)2 + (y0 − b sin t)2 − d




   F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang   ADG 2008
Problem
                                        Our approach
                                             Example
                                         Future work


The distance of a point to an ellipse



  We want to solve a system of equations:
                                            
                                             fd (t) = 0
                                                  ∂fd
                                                      (t)   =0
                                            
                                                   ∂t




   F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang      ADG 2008
Problem
                                        Our approach
                                             Example
                                         Future work


The distance of a point to an ellipse


  We want to solve a system of equations:
                                            
                                             fd (t) = 0
                                                  ∂fd
                                                      (t)   =0
                                            
                                                   ∂t

   There are two posibilities:
      rational change of variable
      complex change of variable



   F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang      ADG 2008
Problem
                                        Our approach
                                             Example
                                         Future work


The distance of a point to an ellipse



  Rational change of variable:
                                                         1−t2
                                              cos t =    1+t2

                                                          2t
                                              sin t =    1+t2

   Disadvantage: more complicated.




   F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang   ADG 2008
Problem
                                        Our approach
                                             Example
                                         Future work


The distance of a point to an ellipse



  Rational change of variable:
                                                         1−t2
                                              cos t =    1+t2

                                                          2t
                                              sin t =    1+t2

   Disadvantage: more complicated.




   F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang   ADG 2008
Problem
                                        Our approach
                                             Example
                                         Future work


The distance of a point to an ellipse



                                                  1
  Since z = cos t + i sin t, z =                  z      and we can use the complex
  change of variable:
                                                                1
                                                            z− z
                                               sin t =       2i

                                                               1
                                                            z+ z
                                               cos t =       2




   F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang      ADG 2008
Problem
                                        Our approach
                                             Example
                                         Future work


The distance of a point to an ellipse


  The new system:


                       √        √            √       √
    (b − a)z 4 + 2(x0 √a − iy0 √b)z 3 − 2(x0 a + iy0 b)z + a − b = 0
   

     (b − a)z 4 − 4(x0 a − iy0 b)z 3 − 2(2(x2 + y0 − d))z 2 +
                                              0
                                                  2
                                                     √
                                             √
                                       +4(x0 a + iy0 b)z + b − a = 0
   



  Using resultants we eliminate the variable z
  (and, as a by-product, i disappears).



   F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang   ADG 2008
Problem
                                        Our approach
                                             Example
                                         Future work


The distance of a point to an ellipse




  Theorem
  If d0 is the distance of a point (x0 , y0 ) to the ellipse ε0 with
                                                      √
                                             √
  center (0, 0) and semiaxes of length a and b then d = d2 is          0
                                                                [x0 ,y ]
  the smallest nonnegative real root of the polynomial F[a,b] 0 (d).




   F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang   ADG 2008
Problem
                                     Our approach
                                          Example
                                      Future work




     [x ,y ]
  F[a,b] 0 (d) =
      0


  = (a − b)2 d4 + 2(a − b)(b2 + 2x2 b + y0 b − 2ay0 − a2 − x2 a)d3
                                             0
                                                      2        2
                                                                              0
  +(y0 b − 8y0 ba − 6b a + 6a y0 − 2x0 a + a + 6x2 y0 b2 − 2y0 b3
       4 2          2 2         2 2        3 2         2 3     4
                                                                        0
                                                                          2       2
        4 2          2 2         3        2 2 2          3        4          2 2
  +6y0 a + 4x0 a b + 2b a + 6x0 y0 a + 2a b − 6x0 ab + 4y0 b a
  +6x4 b2 + 4x4 a2 + 6b3 x2 − 10x2 y0 ab + b4 − 8x2 ab2 − 6y0 ab)d2
        0            0             0        0
                                               2
                                                                0
                                                                             4
           4      4       2 3      4        6 2         2 6    3 2        2     4
  −2(ab + y0 − a b + a b + 2y0 a + 2b x0 − a b − bx0 ay0
       4     2         2    2 2        2 2 2         6      2 4 2         4 3
  −bx0 ay0 + 3x0 ay0 b + 3x0 a y0 b − by0 a + b y0 x0 + 3x0 b
  +3y0 a3 + x2 b4 + x4 a2 y0 − bx6 a − 5x4 ab2 + 3b2 y0 x4 + 3y0 ab2
        4
                   0          0
                                   2
                                          0          0
                                                                   2
                                                                      0
                                                                               4
        2 3 2            4 2         2 2 2         2 3       2 3          2 3
  −2x0 a u0 + 3x0 a b + 3x0 b y0 − 2x0 ab − 2y0 a b − 3y0 ab
  −3x2 a3 b − 2x2 b3 y0 − 5y0 a2 b + 4x2 a2 b2 + 4y0 a2 b2 )d
        0              0
                             2       4
                                                 0
                                                             2

  +(x0 + 2x0 b + b − 2x0 a − 2ba + a + y0 + 2x2 y0 − 2y0 b + 2ay0 )·
       4         2        2       2                2     4
                                                                0
                                                                    2      2       2
     2         2          2
  (bx0 + ay0 − ba) =
         4      [a,b]
  = k=0 hk (x0 , y0 )dk



F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang   ADG 2008
Problem
                                       Our approach
                                            Example
                                        Future work


Remarks to the theorem

                                                        [x ,y ]
        The biggest real root of F[a,b] 0 (d) is the square of the
                                     0


        maximum distance between (x0 , y0 ) and the points in ε0 .
        If x0 is a focus of ε0
                          √
                         [ a−b,0]
                       F[a,b]  (d) = (a − b)2 d2 (d2 + 2(b − 2a)d + b2 )
                              √     √           √     √
                       ⇒ d = ( a − a − b)2 , ( a + a − b)2

        In the case of a circle a = b = R2 and if d = d2
                                                       0
              √
             [ a−b,0]
           F[a,b]       (d2 ) = R4 (y0 + x2 )2 ·
                          0
                                      2
                                          0
                                   2 + 2Rd + R2 − y 2 − x2 )(d2 − 2Rd + R2 − y 2 − x2 )
                               · (d0      0        0     0    0      0        0     0
                 ⇒ d0 = R −           y0 + x2
                                       2
                                            0




  F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang       ADG 2008
Problem
                                       Our approach
                                            Example
                                        Future work


The distance between two ellipses



  Let ε1 be an ellipse disjoint with ε0 , presented by the
  parametrization x = α(s), y = β(s), s ∈ [0, 2π). Then

    d(ε0 , ε1 ) = min{            (x1 − x0 )2 + (y1 − y0 )2 : (xi , yi ) ∈ εi , i = 1, 2}

  is the square root of the smallest nonnegative real root of
                                         [α(s),β(s)]
  the family of univariate polynomials F[a,b]        (d).




  F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang   ADG 2008
Problem
                                       Our approach
                                            Example
                                        Future work


The distance between two ellipses


  In order to determine d(ε0 , ε1 ) we are analyzing two posibilities:
       d is determined as the smallest positive real number s.t.
       there exist s ∈ [0, 2π) solving
                            [α(s),β(s)]           4    [a,b]
                         F[a,b]        =          k=0 hk     (α(s), β(s))dk = 0
                         ¯ [α(s),β(s)] :=
                         F[a,b]
                                                   4   ∂ [a,b]
                                                                (α(s), β(s))dk =
                                                   k=0 ∂s hk                       0

        d is determined by analyzing the implicit curve
          [α(s),β(s)]
        F[a,b]        = 0.




  F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang   ADG 2008
Problem
                                       Our approach
                                            Example
                                        Future work


First case

  Since α(s) and β(s) are linear forms on cos(s) and sin(s) this
  question is converted into an algebraic problem in the same
  way we have proceeded in the case point-ellipse, by performing
  the change of variable

                                 1             1                     1         1
                    cos s =            w+               , sin s =         w−
                                 2             w                     2i        w

  and then using resultants to eliminate w.
  We obtain a univariate polynomial of degree 60, Gε1 , whose
                                                          ε0
  smallest positive real root is the square of d(ε0 , ε1 ).
  Gε1 depends polynomially on the parameters of ε0 and ε1 .
   ε0



  F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang     ADG 2008
Problem
                                       Our approach
                                            Example
                                        Future work


Second case

                                                                             [α(s),β(s)]
  d is determined by analyzing the implicit curve F[a,b]      = 0 in
  the region d ≥ 0 and s ∈ [0, 2π). In order to aply the algorithm
  by L. G ONZALEZ -V EGA , I. N ÉCULA , Efficient topology
  determination of implicitly defined algebraic plane curves.
  Computer Aided Geometric Design, 19: 719-743, 2002, we use
  the change of coordinates:

                                            1 − u2           2u
                              cos s =            2
                                                   sin s =
                                            1+u            1 + u2
                                                            [α(s),β(s)]
  and the real algebraic plane curve F[a,b]                               = 0 is analyzed in
  d ≥ 0, u ∈ R.


  F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang   ADG 2008
Problem
                                       Our approach
                                            Example
                                        Future work


Example




 We consider ε0 and ε1 . ε0 with center (0, 0) and semi-axes of
 length 3 and 2. ε1 centered in (2, −3) and with semi-axes,
 parallel to the coordinate axes, of length 2 and 1.




  F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang   ADG 2008
Problem
                                       Our approach
                                            Example
                                        Future work


Example




  F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang   ADG 2008
Problem
                                       Our approach
                                            Example
                                        Future work


Example




  F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang   ADG 2008
Problem
                                       Our approach
                                            Example
                                        Future work


Example


 In this case the minimum distance is given by computing the
 real roots of the polynomial:
 Gε1 (d) = k1 d4 (d12 −216d11 +...)(d2 −54d+1053)2 (d2 −52d+1700)2 (k2 d12 +k3 d11 +...)3
  ε0


  where ki are real numbers.

 The non multiple factor of degree 12 is the one providing
 the smallest and the biggest nonnegative real roots of
 Gε1 (d). It is not still clear if this pattern appears in a
   ε0
 general way.



  F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang   ADG 2008
Problem
                                       Our approach
                                            Example
                                        Future work


Future work




        Continue studying the continuous motion case.
        Generalize to ellipsoids.
        Non-coplanar ellipses.
        Other conics.




  F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang   ADG 2008
Problem
                                     Our approach
                                          Example
                                      Future work




                                         Thank you!




F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang   ADG 2008

Mais conteúdo relacionado

Mais procurados

Invariant test
Invariant testInvariant test
Invariant testgsangui
 
Elementary Landscape Decomposition of Combinatorial Optimization Problems
Elementary Landscape Decomposition of Combinatorial Optimization ProblemsElementary Landscape Decomposition of Combinatorial Optimization Problems
Elementary Landscape Decomposition of Combinatorial Optimization Problemsjfrchicanog
 
Optimal Finite Difference Grids for Elliptic and Parabolic PDEs with Applicat...
Optimal Finite Difference Grids for Elliptic and Parabolic PDEs with Applicat...Optimal Finite Difference Grids for Elliptic and Parabolic PDEs with Applicat...
Optimal Finite Difference Grids for Elliptic and Parabolic PDEs with Applicat...Alex (Oleksiy) Varfolomiyev
 
Tro07 sparse-solutions-talk
Tro07 sparse-solutions-talkTro07 sparse-solutions-talk
Tro07 sparse-solutions-talkmpbchina
 
GMatasci_Talk_DomainSeparationForEfficientAdaptiveAL_IGARSS2011.pdf
GMatasci_Talk_DomainSeparationForEfficientAdaptiveAL_IGARSS2011.pdfGMatasci_Talk_DomainSeparationForEfficientAdaptiveAL_IGARSS2011.pdf
GMatasci_Talk_DomainSeparationForEfficientAdaptiveAL_IGARSS2011.pdfgrssieee
 
CVPR2010: Advanced ITinCVPR in a Nutshell: part 5: Shape, Matching and Diverg...
CVPR2010: Advanced ITinCVPR in a Nutshell: part 5: Shape, Matching and Diverg...CVPR2010: Advanced ITinCVPR in a Nutshell: part 5: Shape, Matching and Diverg...
CVPR2010: Advanced ITinCVPR in a Nutshell: part 5: Shape, Matching and Diverg...zukun
 
Lesson 16: Inverse Trigonometric Functions
Lesson 16: Inverse Trigonometric FunctionsLesson 16: Inverse Trigonometric Functions
Lesson 16: Inverse Trigonometric FunctionsMatthew Leingang
 
Lesson 23: The Definite Integral (handout)
Lesson 23: The Definite Integral (handout)Lesson 23: The Definite Integral (handout)
Lesson 23: The Definite Integral (handout)Matthew Leingang
 
On Foundations of Parameter Estimation for Generalized Partial Linear Models ...
On Foundations of Parameter Estimation for Generalized Partial Linear Models ...On Foundations of Parameter Estimation for Generalized Partial Linear Models ...
On Foundations of Parameter Estimation for Generalized Partial Linear Models ...SSA KPI
 
Solution of linear and nonlinear partial differential equations using mixture...
Solution of linear and nonlinear partial differential equations using mixture...Solution of linear and nonlinear partial differential equations using mixture...
Solution of linear and nonlinear partial differential equations using mixture...Alexander Decker
 
11.solution of linear and nonlinear partial differential equations using mixt...
11.solution of linear and nonlinear partial differential equations using mixt...11.solution of linear and nonlinear partial differential equations using mixt...
11.solution of linear and nonlinear partial differential equations using mixt...Alexander Decker
 
Jackknife algorithm for the estimation of logistic regression parameters
Jackknife algorithm for the estimation of logistic regression parametersJackknife algorithm for the estimation of logistic regression parameters
Jackknife algorithm for the estimation of logistic regression parametersAlexander Decker
 
Bernheim calculusfinal
Bernheim calculusfinalBernheim calculusfinal
Bernheim calculusfinalrahulrasa
 
Ondelettes, représentations bidimensionnelles, multi-échelles et géométriques...
Ondelettes, représentations bidimensionnelles, multi-échelles et géométriques...Ondelettes, représentations bidimensionnelles, multi-échelles et géométriques...
Ondelettes, représentations bidimensionnelles, multi-échelles et géométriques...Laurent Duval
 
Numerical solution of boundary value problems by piecewise analysis method
Numerical solution of boundary value problems by piecewise analysis methodNumerical solution of boundary value problems by piecewise analysis method
Numerical solution of boundary value problems by piecewise analysis methodAlexander Decker
 
1Sem-Basic Electronics Notes-Unit8-Digital Logic
1Sem-Basic Electronics Notes-Unit8-Digital Logic1Sem-Basic Electronics Notes-Unit8-Digital Logic
1Sem-Basic Electronics Notes-Unit8-Digital LogicDr. Shivananda Koteshwar
 

Mais procurados (17)

Invariant test
Invariant testInvariant test
Invariant test
 
Elementary Landscape Decomposition of Combinatorial Optimization Problems
Elementary Landscape Decomposition of Combinatorial Optimization ProblemsElementary Landscape Decomposition of Combinatorial Optimization Problems
Elementary Landscape Decomposition of Combinatorial Optimization Problems
 
Optimal Finite Difference Grids for Elliptic and Parabolic PDEs with Applicat...
Optimal Finite Difference Grids for Elliptic and Parabolic PDEs with Applicat...Optimal Finite Difference Grids for Elliptic and Parabolic PDEs with Applicat...
Optimal Finite Difference Grids for Elliptic and Parabolic PDEs with Applicat...
 
Tro07 sparse-solutions-talk
Tro07 sparse-solutions-talkTro07 sparse-solutions-talk
Tro07 sparse-solutions-talk
 
GMatasci_Talk_DomainSeparationForEfficientAdaptiveAL_IGARSS2011.pdf
GMatasci_Talk_DomainSeparationForEfficientAdaptiveAL_IGARSS2011.pdfGMatasci_Talk_DomainSeparationForEfficientAdaptiveAL_IGARSS2011.pdf
GMatasci_Talk_DomainSeparationForEfficientAdaptiveAL_IGARSS2011.pdf
 
CVPR2010: Advanced ITinCVPR in a Nutshell: part 5: Shape, Matching and Diverg...
CVPR2010: Advanced ITinCVPR in a Nutshell: part 5: Shape, Matching and Diverg...CVPR2010: Advanced ITinCVPR in a Nutshell: part 5: Shape, Matching and Diverg...
CVPR2010: Advanced ITinCVPR in a Nutshell: part 5: Shape, Matching and Diverg...
 
Lesson 16: Inverse Trigonometric Functions
Lesson 16: Inverse Trigonometric FunctionsLesson 16: Inverse Trigonometric Functions
Lesson 16: Inverse Trigonometric Functions
 
Lesson 23: The Definite Integral (handout)
Lesson 23: The Definite Integral (handout)Lesson 23: The Definite Integral (handout)
Lesson 23: The Definite Integral (handout)
 
On Foundations of Parameter Estimation for Generalized Partial Linear Models ...
On Foundations of Parameter Estimation for Generalized Partial Linear Models ...On Foundations of Parameter Estimation for Generalized Partial Linear Models ...
On Foundations of Parameter Estimation for Generalized Partial Linear Models ...
 
Linear Algebra
Linear AlgebraLinear Algebra
Linear Algebra
 
Solution of linear and nonlinear partial differential equations using mixture...
Solution of linear and nonlinear partial differential equations using mixture...Solution of linear and nonlinear partial differential equations using mixture...
Solution of linear and nonlinear partial differential equations using mixture...
 
11.solution of linear and nonlinear partial differential equations using mixt...
11.solution of linear and nonlinear partial differential equations using mixt...11.solution of linear and nonlinear partial differential equations using mixt...
11.solution of linear and nonlinear partial differential equations using mixt...
 
Jackknife algorithm for the estimation of logistic regression parameters
Jackknife algorithm for the estimation of logistic regression parametersJackknife algorithm for the estimation of logistic regression parameters
Jackknife algorithm for the estimation of logistic regression parameters
 
Bernheim calculusfinal
Bernheim calculusfinalBernheim calculusfinal
Bernheim calculusfinal
 
Ondelettes, représentations bidimensionnelles, multi-échelles et géométriques...
Ondelettes, représentations bidimensionnelles, multi-échelles et géométriques...Ondelettes, représentations bidimensionnelles, multi-échelles et géométriques...
Ondelettes, représentations bidimensionnelles, multi-échelles et géométriques...
 
Numerical solution of boundary value problems by piecewise analysis method
Numerical solution of boundary value problems by piecewise analysis methodNumerical solution of boundary value problems by piecewise analysis method
Numerical solution of boundary value problems by piecewise analysis method
 
1Sem-Basic Electronics Notes-Unit8-Digital Logic
1Sem-Basic Electronics Notes-Unit8-Digital Logic1Sem-Basic Electronics Notes-Unit8-Digital Logic
1Sem-Basic Electronics Notes-Unit8-Digital Logic
 

Destaque

Parental Contact Resistance
Parental Contact ResistanceParental Contact Resistance
Parental Contact ResistanceValerie Houghton
 
Facebook by Crystal
Facebook by CrystalFacebook by Crystal
Facebook by Crystalcrystalligda
 
Biology Vocabulary Round 1
Biology Vocabulary Round 1Biology Vocabulary Round 1
Biology Vocabulary Round 1ktini
 
Finansmatematik- offer eller orsak i finanskrisen?
Finansmatematik- offer eller orsak i finanskrisen?Finansmatematik- offer eller orsak i finanskrisen?
Finansmatematik- offer eller orsak i finanskrisen?Salla Franzén
 

Destaque (10)

58 hawalah bil-ujrah
58 hawalah bil-ujrah58 hawalah bil-ujrah
58 hawalah bil-ujrah
 
Parental Contact Resistance
Parental Contact ResistanceParental Contact Resistance
Parental Contact Resistance
 
Blogging: What I've Learned
Blogging: What I've LearnedBlogging: What I've Learned
Blogging: What I've Learned
 
Facebook by Crystal
Facebook by CrystalFacebook by Crystal
Facebook by Crystal
 
Biology Vocabulary Round 1
Biology Vocabulary Round 1Biology Vocabulary Round 1
Biology Vocabulary Round 1
 
Arquitectura pp01(a 3) (1)
Arquitectura pp01(a 3) (1)Arquitectura pp01(a 3) (1)
Arquitectura pp01(a 3) (1)
 
Metapop Case Study
Metapop Case StudyMetapop Case Study
Metapop Case Study
 
Finansmatematik- offer eller orsak i finanskrisen?
Finansmatematik- offer eller orsak i finanskrisen?Finansmatematik- offer eller orsak i finanskrisen?
Finansmatematik- offer eller orsak i finanskrisen?
 
Mehanic energy 10 r angi.pptx
Mehanic energy 10 r angi.pptxMehanic energy 10 r angi.pptx
Mehanic energy 10 r angi.pptx
 
Galois evariste
Galois evaristeGalois evariste
Galois evariste
 

Semelhante a ADG 2008

Semelhante a ADG 2008 (9)

CIEM 07
CIEM 07CIEM 07
CIEM 07
 
CGTA09
CGTA09CGTA09
CGTA09
 
In792(2)
In792(2)In792(2)
In792(2)
 
SIAMGD09
SIAMGD09SIAMGD09
SIAMGD09
 
Introduction of Inverse Problem and Its Applications
Introduction of Inverse Problem and Its ApplicationsIntroduction of Inverse Problem and Its Applications
Introduction of Inverse Problem and Its Applications
 
nonlinear_rmt.pdf
nonlinear_rmt.pdfnonlinear_rmt.pdf
nonlinear_rmt.pdf
 
Random Matrix Theory and Machine Learning - Part 4
Random Matrix Theory and Machine Learning - Part 4Random Matrix Theory and Machine Learning - Part 4
Random Matrix Theory and Machine Learning - Part 4
 
MUMS: Bayesian, Fiducial, and Frequentist Conference - Model Selection in the...
MUMS: Bayesian, Fiducial, and Frequentist Conference - Model Selection in the...MUMS: Bayesian, Fiducial, and Frequentist Conference - Model Selection in the...
MUMS: Bayesian, Fiducial, and Frequentist Conference - Model Selection in the...
 
Macrocanonical models for texture synthesis
Macrocanonical models for texture synthesisMacrocanonical models for texture synthesis
Macrocanonical models for texture synthesis
 

Mais de Gema R. Quintana

Pechakucha Congreso DIMA 2018
Pechakucha Congreso DIMA 2018Pechakucha Congreso DIMA 2018
Pechakucha Congreso DIMA 2018Gema R. Quintana
 
Motivos para el uso de Instagram en los Adolescentes
Motivos para el uso de Instagram en los AdolescentesMotivos para el uso de Instagram en los Adolescentes
Motivos para el uso de Instagram en los AdolescentesGema R. Quintana
 
Motivos para el uso de Instagram en los Adolescentes
Motivos para el uso de Instagram en los AdolescentesMotivos para el uso de Instagram en los Adolescentes
Motivos para el uso de Instagram en los AdolescentesGema R. Quintana
 
Intersección medicina y matemáticas
Intersección medicina y matemáticasIntersección medicina y matemáticas
Intersección medicina y matemáticasGema R. Quintana
 
Introduction to Lie Groups
Introduction to Lie GroupsIntroduction to Lie Groups
Introduction to Lie GroupsGema R. Quintana
 
Presentation of my Master's Thesis
Presentation of my Master's ThesisPresentation of my Master's Thesis
Presentation of my Master's ThesisGema R. Quintana
 
Master's Thesis: Closed formulae for distance functions involving ellipses.
Master's Thesis: Closed formulae for distance functions involving ellipses.Master's Thesis: Closed formulae for distance functions involving ellipses.
Master's Thesis: Closed formulae for distance functions involving ellipses.Gema R. Quintana
 
VXC: Computer Vision Presentation
VXC: Computer Vision PresentationVXC: Computer Vision Presentation
VXC: Computer Vision PresentationGema R. Quintana
 

Mais de Gema R. Quintana (14)

Pechakucha Congreso DIMA 2018
Pechakucha Congreso DIMA 2018Pechakucha Congreso DIMA 2018
Pechakucha Congreso DIMA 2018
 
Motivos para el uso de Instagram en los Adolescentes
Motivos para el uso de Instagram en los AdolescentesMotivos para el uso de Instagram en los Adolescentes
Motivos para el uso de Instagram en los Adolescentes
 
Motivos para el uso de Instagram en los Adolescentes
Motivos para el uso de Instagram en los AdolescentesMotivos para el uso de Instagram en los Adolescentes
Motivos para el uso de Instagram en los Adolescentes
 
Creativity is...
Creativity is...Creativity is...
Creativity is...
 
Intersección medicina y matemáticas
Intersección medicina y matemáticasIntersección medicina y matemáticas
Intersección medicina y matemáticas
 
Introduction to Lie Groups
Introduction to Lie GroupsIntroduction to Lie Groups
Introduction to Lie Groups
 
Presentation of my Master's Thesis
Presentation of my Master's ThesisPresentation of my Master's Thesis
Presentation of my Master's Thesis
 
Master's Thesis: Closed formulae for distance functions involving ellipses.
Master's Thesis: Closed formulae for distance functions involving ellipses.Master's Thesis: Closed formulae for distance functions involving ellipses.
Master's Thesis: Closed formulae for distance functions involving ellipses.
 
VXC: Computer Vision Presentation
VXC: Computer Vision PresentationVXC: Computer Vision Presentation
VXC: Computer Vision Presentation
 
VXC: Computer Vision
VXC: Computer VisionVXC: Computer Vision
VXC: Computer Vision
 
Real Surfaces
Real SurfacesReal Surfaces
Real Surfaces
 
Real Surfaces
Real SurfacesReal Surfaces
Real Surfaces
 
CVC Seminar
CVC SeminarCVC Seminar
CVC Seminar
 
ADG08
ADG08ADG08
ADG08
 

Último

Incoming and Outgoing Shipments in 1 STEP Using Odoo 17
Incoming and Outgoing Shipments in 1 STEP Using Odoo 17Incoming and Outgoing Shipments in 1 STEP Using Odoo 17
Incoming and Outgoing Shipments in 1 STEP Using Odoo 17Celine George
 
Presiding Officer Training module 2024 lok sabha elections
Presiding Officer Training module 2024 lok sabha electionsPresiding Officer Training module 2024 lok sabha elections
Presiding Officer Training module 2024 lok sabha electionsanshu789521
 
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxPOINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxSayali Powar
 
Introduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxIntroduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxpboyjonauth
 
Alper Gobel In Media Res Media Component
Alper Gobel In Media Res Media ComponentAlper Gobel In Media Res Media Component
Alper Gobel In Media Res Media ComponentInMediaRes1
 
microwave assisted reaction. General introduction
microwave assisted reaction. General introductionmicrowave assisted reaction. General introduction
microwave assisted reaction. General introductionMaksud Ahmed
 
How to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptxHow to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptxmanuelaromero2013
 
CARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptxCARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptxGaneshChakor2
 
Separation of Lanthanides/ Lanthanides and Actinides
Separation of Lanthanides/ Lanthanides and ActinidesSeparation of Lanthanides/ Lanthanides and Actinides
Separation of Lanthanides/ Lanthanides and ActinidesFatimaKhan178732
 
18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdf
18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdf18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdf
18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdfssuser54595a
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)eniolaolutunde
 
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Sapana Sha
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeThiyagu K
 
Concept of Vouching. B.Com(Hons) /B.Compdf
Concept of Vouching. B.Com(Hons) /B.CompdfConcept of Vouching. B.Com(Hons) /B.Compdf
Concept of Vouching. B.Com(Hons) /B.CompdfUmakantAnnand
 
Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991
Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991
Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991RKavithamani
 
_Math 4-Q4 Week 5.pptx Steps in Collecting Data
_Math 4-Q4 Week 5.pptx Steps in Collecting Data_Math 4-Q4 Week 5.pptx Steps in Collecting Data
_Math 4-Q4 Week 5.pptx Steps in Collecting DataJhengPantaleon
 
APM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across SectorsAPM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across SectorsAssociation for Project Management
 
URLs and Routing in the Odoo 17 Website App
URLs and Routing in the Odoo 17 Website AppURLs and Routing in the Odoo 17 Website App
URLs and Routing in the Odoo 17 Website AppCeline George
 

Último (20)

Incoming and Outgoing Shipments in 1 STEP Using Odoo 17
Incoming and Outgoing Shipments in 1 STEP Using Odoo 17Incoming and Outgoing Shipments in 1 STEP Using Odoo 17
Incoming and Outgoing Shipments in 1 STEP Using Odoo 17
 
Presiding Officer Training module 2024 lok sabha elections
Presiding Officer Training module 2024 lok sabha electionsPresiding Officer Training module 2024 lok sabha elections
Presiding Officer Training module 2024 lok sabha elections
 
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxPOINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
 
Introduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxIntroduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptx
 
Alper Gobel In Media Res Media Component
Alper Gobel In Media Res Media ComponentAlper Gobel In Media Res Media Component
Alper Gobel In Media Res Media Component
 
microwave assisted reaction. General introduction
microwave assisted reaction. General introductionmicrowave assisted reaction. General introduction
microwave assisted reaction. General introduction
 
How to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptxHow to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptx
 
CARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptxCARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptx
 
Separation of Lanthanides/ Lanthanides and Actinides
Separation of Lanthanides/ Lanthanides and ActinidesSeparation of Lanthanides/ Lanthanides and Actinides
Separation of Lanthanides/ Lanthanides and Actinides
 
18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdf
18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdf18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdf
18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdf
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)
 
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and Mode
 
Concept of Vouching. B.Com(Hons) /B.Compdf
Concept of Vouching. B.Com(Hons) /B.CompdfConcept of Vouching. B.Com(Hons) /B.Compdf
Concept of Vouching. B.Com(Hons) /B.Compdf
 
Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991
Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991
Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991
 
_Math 4-Q4 Week 5.pptx Steps in Collecting Data
_Math 4-Q4 Week 5.pptx Steps in Collecting Data_Math 4-Q4 Week 5.pptx Steps in Collecting Data
_Math 4-Q4 Week 5.pptx Steps in Collecting Data
 
TataKelola dan KamSiber Kecerdasan Buatan v022.pdf
TataKelola dan KamSiber Kecerdasan Buatan v022.pdfTataKelola dan KamSiber Kecerdasan Buatan v022.pdf
TataKelola dan KamSiber Kecerdasan Buatan v022.pdf
 
APM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across SectorsAPM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across Sectors
 
URLs and Routing in the Odoo 17 Website App
URLs and Routing in the Odoo 17 Website AppURLs and Routing in the Odoo 17 Website App
URLs and Routing in the Odoo 17 Website App
 
Código Creativo y Arte de Software | Unidad 1
Código Creativo y Arte de Software | Unidad 1Código Creativo y Arte de Software | Unidad 1
Código Creativo y Arte de Software | Unidad 1
 

ADG 2008

  • 1. Problem Our approach Example Future work Closed formulae for distance functions involving ellipses. F. Etayo1 , L. Gonzalez-Vega1 , G. R. Quintana1 , W. Wang2 1 Departamento de Matemáticas, Estadística y Computación Universidad de Cantabria 2 Department of Computer Science University of Hong Kong VII International Workshop on Automated Deduction in Geometry F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 2. Problem Our approach Example Future work Contents 1 Problem 2 Our approach 3 Example 4 Future work F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 3. Problem Our approach Example Future work Introduction We want to compute the distance between two coplanar ellipses. The minimum distance between a given point and one ellipse is a positive algebraic number: our goal is to determine a polynomial with this number as a real root. This way of presenting the distance is independent of the corresponding footpoints and provides the distance directly. We can use this formula for analyzing the Ellipses Moving Problem (EMP). F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 4. Problem Our approach Example Future work Applications The computation of the minimum distance between two ellipses (static or dynamic) is a fundamental task in various applications: collision detection in robotics, interference avoidance in CAD/CAM, interactions in virtual reality, computer games, orbit analysis (non-coplanar ellipses), interference analysis of molecules in computational physics and chemistry, etc. F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 5. Problem Our approach Example Future work Previous works I. Z. E MIRIS , E. T SIGARIDAS , G. M. T ZOUMAS . The predicates for the Voronoi diagram of ellipses. Proc. ACM Symp. Comput. Geom., 2006. I. Z. E MIRIS , G. M. T ZOUMAS . A Real-time and Exact Implementation of the predicates for the Voronoi Diagram for parametric ellipses. Proc. ACM Symp. Solid Physical Modelling, 2007. C. L ENNERZ , E. S CHÖMER . Efficient Distance Computation for Quadratic Curves and Surfaces. Geometric Modelling and Processing Proceedings, 2002. F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 6. Problem Our approach Example Future work Previous works J.-K. S EONG , D. E. J OHNSON , E. C OHEN . A Higher Dimensional Formulation for Robust and Interactive Distance Queries. Proc. ACM Solid and Physical Modeling, 2006. K.A. S OHN , B. J ÜTTLER , M.S. K IM , W. WANG . Computing the Distance Between Two Surfaces via Line Geometry. Proc. Tenth Pacific Conference on Computer Graphics and Applications, 236-245, IEEE Press, 2002. Common aspect: the problem is always solved by determining, first, the footpoints and then the searched distance. F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 7. Problem Our approach Example Future work Our approach We do not make the minimum distance computation depending on the determination of the footpoints. We study the ellipse separation problem by analyzing the univariate polynomial providing the distance. Parameters of our problem: center coordinates, axes length, inclination of the axes. F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 8. Problem Our approach Example Future work Our approach We do not make the minimum distance computation depending on the determination of the footpoints. We study the ellipse separation problem by analyzing the univariate polynomial providing the distance. Parameters of our problem: center coordinates, axes length, inclination of the axes. Is there any advantage? F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 9. Problem Our approach Example Future work Our approach We do not make the minimum distance computation depending on the determination of the footpoints. We study the ellipse separation problem by analyzing the univariate polynomial providing the distance. Parameters of our problem: center coordinates, axes length, inclination of the axes. Is there any advantage? Indeed: the distance behaves continuously but footpoints do not. F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 10. Problem Our approach Example Future work The distance of a point to an ellipse We consider the parametric equations of an ellipse, ε0 : √ √ x = a cos t, y = b sin t, t ∈ [0, 2π) in order to construct a function fd whose minimum positive value, d, gives the square of the distance between a point (x0 , y0 ) and the ellipse: √ √ fd := (x0 − a cos t)2 + (y0 − b sin t)2 − d F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 11. Problem Our approach Example Future work The distance of a point to an ellipse We want to solve a system of equations:   fd (t) = 0 ∂fd (t) =0  ∂t F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 12. Problem Our approach Example Future work The distance of a point to an ellipse We want to solve a system of equations:   fd (t) = 0 ∂fd (t) =0  ∂t There are two posibilities: rational change of variable complex change of variable F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 13. Problem Our approach Example Future work The distance of a point to an ellipse Rational change of variable: 1−t2 cos t = 1+t2 2t sin t = 1+t2 Disadvantage: more complicated. F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 14. Problem Our approach Example Future work The distance of a point to an ellipse Rational change of variable: 1−t2 cos t = 1+t2 2t sin t = 1+t2 Disadvantage: more complicated. F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 15. Problem Our approach Example Future work The distance of a point to an ellipse 1 Since z = cos t + i sin t, z = z and we can use the complex change of variable: 1 z− z sin t = 2i 1 z+ z cos t = 2 F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 16. Problem Our approach Example Future work The distance of a point to an ellipse The new system: √ √ √ √  (b − a)z 4 + 2(x0 √a − iy0 √b)z 3 − 2(x0 a + iy0 b)z + a − b = 0  (b − a)z 4 − 4(x0 a − iy0 b)z 3 − 2(2(x2 + y0 − d))z 2 + 0 2 √ √ +4(x0 a + iy0 b)z + b − a = 0  Using resultants we eliminate the variable z (and, as a by-product, i disappears). F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 17. Problem Our approach Example Future work The distance of a point to an ellipse Theorem If d0 is the distance of a point (x0 , y0 ) to the ellipse ε0 with √ √ center (0, 0) and semiaxes of length a and b then d = d2 is 0 [x0 ,y ] the smallest nonnegative real root of the polynomial F[a,b] 0 (d). F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 18. Problem Our approach Example Future work [x ,y ] F[a,b] 0 (d) = 0 = (a − b)2 d4 + 2(a − b)(b2 + 2x2 b + y0 b − 2ay0 − a2 − x2 a)d3 0 2 2 0 +(y0 b − 8y0 ba − 6b a + 6a y0 − 2x0 a + a + 6x2 y0 b2 − 2y0 b3 4 2 2 2 2 2 3 2 2 3 4 0 2 2 4 2 2 2 3 2 2 2 3 4 2 2 +6y0 a + 4x0 a b + 2b a + 6x0 y0 a + 2a b − 6x0 ab + 4y0 b a +6x4 b2 + 4x4 a2 + 6b3 x2 − 10x2 y0 ab + b4 − 8x2 ab2 − 6y0 ab)d2 0 0 0 0 2 0 4 4 4 2 3 4 6 2 2 6 3 2 2 4 −2(ab + y0 − a b + a b + 2y0 a + 2b x0 − a b − bx0 ay0 4 2 2 2 2 2 2 2 6 2 4 2 4 3 −bx0 ay0 + 3x0 ay0 b + 3x0 a y0 b − by0 a + b y0 x0 + 3x0 b +3y0 a3 + x2 b4 + x4 a2 y0 − bx6 a − 5x4 ab2 + 3b2 y0 x4 + 3y0 ab2 4 0 0 2 0 0 2 0 4 2 3 2 4 2 2 2 2 2 3 2 3 2 3 −2x0 a u0 + 3x0 a b + 3x0 b y0 − 2x0 ab − 2y0 a b − 3y0 ab −3x2 a3 b − 2x2 b3 y0 − 5y0 a2 b + 4x2 a2 b2 + 4y0 a2 b2 )d 0 0 2 4 0 2 +(x0 + 2x0 b + b − 2x0 a − 2ba + a + y0 + 2x2 y0 − 2y0 b + 2ay0 )· 4 2 2 2 2 4 0 2 2 2 2 2 2 (bx0 + ay0 − ba) = 4 [a,b] = k=0 hk (x0 , y0 )dk F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 19. Problem Our approach Example Future work Remarks to the theorem [x ,y ] The biggest real root of F[a,b] 0 (d) is the square of the 0 maximum distance between (x0 , y0 ) and the points in ε0 . If x0 is a focus of ε0 √ [ a−b,0] F[a,b] (d) = (a − b)2 d2 (d2 + 2(b − 2a)d + b2 ) √ √ √ √ ⇒ d = ( a − a − b)2 , ( a + a − b)2 In the case of a circle a = b = R2 and if d = d2 0 √ [ a−b,0] F[a,b] (d2 ) = R4 (y0 + x2 )2 · 0 2 0 2 + 2Rd + R2 − y 2 − x2 )(d2 − 2Rd + R2 − y 2 − x2 ) · (d0 0 0 0 0 0 0 0 ⇒ d0 = R − y0 + x2 2 0 F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 20. Problem Our approach Example Future work The distance between two ellipses Let ε1 be an ellipse disjoint with ε0 , presented by the parametrization x = α(s), y = β(s), s ∈ [0, 2π). Then d(ε0 , ε1 ) = min{ (x1 − x0 )2 + (y1 − y0 )2 : (xi , yi ) ∈ εi , i = 1, 2} is the square root of the smallest nonnegative real root of [α(s),β(s)] the family of univariate polynomials F[a,b] (d). F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 21. Problem Our approach Example Future work The distance between two ellipses In order to determine d(ε0 , ε1 ) we are analyzing two posibilities: d is determined as the smallest positive real number s.t. there exist s ∈ [0, 2π) solving [α(s),β(s)] 4 [a,b] F[a,b] = k=0 hk (α(s), β(s))dk = 0 ¯ [α(s),β(s)] := F[a,b] 4 ∂ [a,b] (α(s), β(s))dk = k=0 ∂s hk 0 d is determined by analyzing the implicit curve [α(s),β(s)] F[a,b] = 0. F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 22. Problem Our approach Example Future work First case Since α(s) and β(s) are linear forms on cos(s) and sin(s) this question is converted into an algebraic problem in the same way we have proceeded in the case point-ellipse, by performing the change of variable 1 1 1 1 cos s = w+ , sin s = w− 2 w 2i w and then using resultants to eliminate w. We obtain a univariate polynomial of degree 60, Gε1 , whose ε0 smallest positive real root is the square of d(ε0 , ε1 ). Gε1 depends polynomially on the parameters of ε0 and ε1 . ε0 F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 23. Problem Our approach Example Future work Second case [α(s),β(s)] d is determined by analyzing the implicit curve F[a,b] = 0 in the region d ≥ 0 and s ∈ [0, 2π). In order to aply the algorithm by L. G ONZALEZ -V EGA , I. N ÉCULA , Efficient topology determination of implicitly defined algebraic plane curves. Computer Aided Geometric Design, 19: 719-743, 2002, we use the change of coordinates: 1 − u2 2u cos s = 2 sin s = 1+u 1 + u2 [α(s),β(s)] and the real algebraic plane curve F[a,b] = 0 is analyzed in d ≥ 0, u ∈ R. F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 24. Problem Our approach Example Future work Example We consider ε0 and ε1 . ε0 with center (0, 0) and semi-axes of length 3 and 2. ε1 centered in (2, −3) and with semi-axes, parallel to the coordinate axes, of length 2 and 1. F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 25. Problem Our approach Example Future work Example F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 26. Problem Our approach Example Future work Example F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 27. Problem Our approach Example Future work Example In this case the minimum distance is given by computing the real roots of the polynomial: Gε1 (d) = k1 d4 (d12 −216d11 +...)(d2 −54d+1053)2 (d2 −52d+1700)2 (k2 d12 +k3 d11 +...)3 ε0 where ki are real numbers. The non multiple factor of degree 12 is the one providing the smallest and the biggest nonnegative real roots of Gε1 (d). It is not still clear if this pattern appears in a ε0 general way. F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 28. Problem Our approach Example Future work Future work Continue studying the continuous motion case. Generalize to ellipsoids. Non-coplanar ellipses. Other conics. F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008
  • 29. Problem Our approach Example Future work Thank you! F. Etayo, L. Gonzalez-Vega, G. R. Quintana, W. Wang ADG 2008