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2.1 Geometric primitives and transformations                                            33



                                      y                                  projective
                                                           similarity
                                           translation


                                                   Euclidean       affine
                                                                                  x


               Figure 2.4 Basic set of 2D planar transformations.



               3D quadrics.  The 3D analog of a conic section is a quadric surface

                                                 T
                                                ¯ x Q¯x =0                          (2.13)
               (Hartley and Zisserman 2004, Chapter 2). Again, while quadric surfaces are useful in the
               study of multi-view geometry and can also serve as useful modeling primitives (spheres,
               ellipsoids, cylinders), we do not study them in great detail in this book.


               2.1.2 2D transformations

               Having defined our basic primitives, we can now turn our attention to how they can be trans-
               formed. The simplest transformations occur in the 2D plane and are illustrated in Figure 2.4.


               Translation.  2D translations can be written as x = x + t or


                                             x =     I  t     ¯ x                   (2.14)
               where I is the (2 × 2) identity matrix or

                                                    I   t

                                             ¯ x =         ¯ x                      (2.15)
                                                   0 T  1
               where 0 is the zero vector. Using a 2 × 3 matrix results in a more compact notation, whereas
               using a full-rank 3 × 3 matrix (which can be obtained from the 2 × 3 matrix by appending a
                 T
               [0 1] row) makes it possible to chain transformations using matrix multiplication. Note that
               in any equation where an augmented vector such as ¯x appears on both sides, it can always be
               replaced with a full homogeneous vector ˜x.


               Rotation + translation. This transformation is also known as 2D rigid body motion or
               the 2D Euclidean transformation (since Euclidean distances are preserved). It can be written
               as x = Rx + t or


                                             x =     R  t     ¯ x                   (2.16)
               where

                                                 cos θ  − sin θ
                                          R =                                       (2.17)
                                                 sin θ  cos θ
                                                  T
               is an orthonormal rotation matrix with RR = I and |R| =1.
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