M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion Robotica e Sensor Fusion per i Sistemi...
-
Upload
diana-moser -
Category
Documents
-
view
215 -
download
2
Transcript of M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion Robotica e Sensor Fusion per i Sistemi...
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Robotica e Sensor Fusion per i Sistemi Meccatronici
Object Detection with Superquadrics
Prof. Mariolino De Cecco, Dr. Ilya Afanasyev, Ing. Nicolo Biasi
Department of Structural Mechanical Engineering, University of Trento
Email: [email protected]
http://www.mariolinodececco.altervista.org/
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Examples of Superquadrics
Examples of Superquadrics
[1]
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Examples of Superquadrics
Wireframes of Superquadrics
[1]
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Definition of Superquadrics
Figures from Superquadrics
[3]
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
About Superquadrics
About SuperquadricsThe term of Superquadrics was defined by Alan Barr in 1981 [2]. Superquadrics are a flexible family of 3D parametric objects, useful for geometric modeling. By adjusting a relatively few number of parameters, a large variety of shapes may be obtained. A particularly attractive feature of superquadrics is their simple mathematical representation.
Superquadrics are used as primitives for shape representation and play the role of prototypical parts and can be further deformed and glued together into realistic looking models.
[9]
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Classification of Superquadrics [2,9]
Classification of Superquadrics
a) Superellipsoids.
b) Superhyperboloids of one piece.
c) Superhyperboloids of two pieces.
d) Supertoroids.
a) b) c)
d)[9]
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Definition of Spherical Products
Definition of Spherical Products
Example. For two 2D curves: circle and parabola, the spherical product is 3D paraboloid.
For two 2x1 vectors [a b]’ and [c d]’ the spherical product is 3x1 vector for which:
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Spherical Products [9]
Spherical ProductsA 3D surface can be obtained by the spherical product of two 2D curves [2]. The spherical product is defined to operate on two 2D curves. A unit sphere is produced by a spherical product of a circle h(ω) horizontally and a half circle m(η) vertically.
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Superellipsoids
The equation of Superellipse is
Spherical Products for Superellipsoids
and in parametric form:
Superellipsoids can be obtained by a spherical products of a pair of such superellipses:
The implicit equation is:
- are parameters of shape squareness;
a1 a2 a3 - parameters of Superellipsoid sizes.
1 2where
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Vector r(η,ω) sweeps out a closed surface in space when η,ω change in the given intervals:
η
ω
x
y
z
r(η,ω)
Creation of Superellipsoids in spherical coordinates
η,ω – independent parameters (latitude and longitude angles) of vector r(η,ω) expressed in spherical coordinates.
2
2
r ( )
a1cos ( )1cos ( )
2
a2cos ( )1sin ( )
2
a3sin ( )1
a1
a2
a3
Superellipsoids
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
x,y – independent parameters (Cartesian coordinates of SQ) are used to obtain z.
f x y z( )x
a1
2
2y
a2
2
2
21
z
a3
2
1
Use the implicit equation in Cartesian coordinates, considering
f(x,y,z) = 1-a1 ≤ x ≤ a1
-a2 ≤ y ≤ a2
05/04/2011 11/20
x’
x
y
z
y’
z’
z=NaN
y=a2
x=a1
Creation of Superellipsoids in Cartesian coordinates
The implicit form is important for the recovery of Superquadrics and testing for intersections, while the explicit form is more suitable for scene reconstruction and rendering.
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Warning: complex numbers in SQ equation
1. If ε1 or ε2 < 1 and cos or sin of angles ω or η < 0, then vector r(η,ω) has complex values. To escape them, it should be used signum-function of sin or cos and absolute values of the vector components.
2
2
2. Analogically if x or y < 1 and ε1 > 1, the function f(x,y,z) willl have the complex values of z. To overcome it, use the f(x,y,z) in power of exponent ε1.
f x y z( )x
a1
2
2y
a2
2
2
21
z
a3
2
1
f(x,y,z)ε1 = 1
12/20
05/04/2011
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Examples of Superellipsoids
Examples of Superellipsoids
[4]
Superellipsoids can model spheres, cylinders, parallelepipeds and shapes in between. Modeling capabilities can be enhanced by tapering, bending and making cavities.
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
What ε1 and ε2 mean?
ε1 = 0.1 ε1 = 1 ε1 = 2
ε2 = 0.1
ε2 = 1
ε2 = 2
[9]
05/04/2011 14/20
ε1 and ε2 – are parameters of shape squareness.
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Superellipsoids shapes varying from ε1, ε2
05/04/2011 15/20
ε1 = 3
ε2 = 1
ε1 = 1
ε2 = 3
ε1 = 3
ε2 = 3
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
What a1, a2 and a3 mean?
05/04/2011 16/20
a1, a2 and a3 – are parameters of parallelepiped’s semi-sides.
The parameters of shape squareness for parallelepiped are: ε1 = ε1 = 0.1
If parallelepiped has dimensions: 20 x 30 x 10 cm, it means that a1 = 10, a2 = 15 and a3 = 5.
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Superhyperboloids of one piece
Spherical Products for Superhyperboloids of one piece
Superhyperboloids of one piece can be obtained by a spherical products of a hyperboloid and a superellipse:
The implicit equation is:
- are parameters of shape squareness;
a1 a2 a3 - parameters of Superellipsoid sizes.
1 2where
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Superhyperboloids of two pieces
Spherical Products for Superhyperboloids of two pieces
Superhyperboloids of two pieces can be obtained by a spherical products of a pair of such hyperboloids:
The implicit equation is:
- are parameters of shape squareness;
a1 a2 a3 - parameters of Superellipsoid sizes.
1 2where
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Supertoroids
Spherical Products for Supertoroids
Supertoroids can be obtained by a spherical products of the following surface vectors:
The implicit equation is:
- are parameters of shape squareness;
- parameters of Superellipsoid sizes.
1 2where
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Rotation and translation of SQ
Elevation
Azimuth
x
y
z
zW
xW
yW
T – transformation matrix.n – amounts of points in SQ surface.
SQ – coordinates of points of SQ surface. Pw – coordinates of points of rotated SQ surface.
xW, yW, zW – world system of coordinates (with center in viewpoint).
05/04/2011 21/20
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Elevation
Azimuth
x
y
z
zW
xW
yW
Rotation and translation of SQ
px
az,el,px,py,pz,x,y,z – are given; xW,yW,zW – should be found.
T SQ Pw
05/04/2011 22/20
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Applications with SuperquadricsSuperquadrics have been employed in computer vision and robotics problems related to object recognition. Superquadrics can be used for
1. Object recognition by fitting geometric shapes to 3D sensor data obtained by a robot.
Shape reconstruction is a low level process where sensor data is interpreted to regenerate objects in a scene making as few assumptions as possible about the objects. Object recognition is a higher level process whose goal is to abstract from the detailed data in order to characterize objects in a scene.
2. Scene reconstruction and recognition. Rendering.
In order to fit a superquadric to a surface region, 11 parameters must be determined: three extent parameters (a1, a2, a3), two shape parameters (ε1 and ε2), three translation parameters, and three rotation parameters.
Applications with Superquadrics
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Reconstruction of complex object [6]
Applications with SQ
Reconstruction of complex object [8]
Reconstruction of complex object [7]
05/04/2011 24/20
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Reconstruction of multiple objects [9]
Applications with SQ
Reconstruction of multiple objects [9]
05/04/2011 25/20
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Links1. A. Skowronski, J. Feldman. Superquadrics. cs557 Project, McGill University.
http://www.skowronski.ca/andrew/school/557/start.html
2. Barr A.H. Superquadrics and Angle-Preserving Transformations. IEEE Computer Graphics and Applications, 1, 11-22. 1981.
3. Chevalier L., etc. Segmentation and superquadric modeling of 3D objects. Journal of WSCG, V.11 (1), 2003. ISSN 1213-6972.
4. Kindlmann G. Superquadric Tensor Glyphs. EUROGRAPHICS. IEEE TCVG Symposium on Visualization (2004). Pages 8.
5. Solina F. and Bajcsy R. Recovery of parametric models from range images: The case for superquadrics with global deformations. // IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-12(2):131--147, 1990.
6. Chella A. and Pirrone R. A Neural Architecture for Segmentation and Modeling of Range Data. // 10 pages.
7. Leonardis A., Jaklic A., and Solina F. Superquadrics for Segmenting and Modeling Range Data. // IEEE Transactions On Pattern Analysis And Machine Intelligence, vol. 19, no. 11, 1997.
8. Bhabhrawala T., Krovi V., Mendel F. and Govindaraju V. Extended Superquadrics. // Technical Report. New York, 2007. 93 pages.
9. Jaklic Ales, Leonardis Ales, Solina Franc. Segmentation and Recovery of Superquadrics. // Computational imaging and vision 20, Kluwer, Dordrecht, 2000.
Grazie per attenzione!!