# Traslation

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Technology

Published on March 13, 2014

Author: shehrevard

Source: slideshare.net

## Description

computer graphics, drawing

1 Transformations

2 Objectives • Introduce affine transformations ­ Translation ­ Rotation ­ Scaling • Derive homogeneous coordinate transformation matrices • Learn to build arbitrary transformation matrices from simple transformations

3 General Transformations • A transformation maps points to other points and/or vectors to other vectors • (x,y,z) ­> (x’,y’,z’) • Affine transformations such as translation, rotation and scaling are line preserving • These rigid body transformations are used widely in computer graphics

4 Translation • Translate the (x,y,z) coordinates of all points on an object to by displacement d object

5 Translation • Translate a point P=(x,y,z) to a new location P’=(x’,y’,z’) • Displacement given by vector d=(dx,dy,dz) • Hence P’=(x’,y’,z’) = (x+dx, y+dy, z+dz) P P’ d

6 Translation • Translation can be expressed in terms of a matrix multiplication by representing 3D points (x,y,z) in Homogeneous coordinates (x,y,z,1)                         = 11000 d100 d010 d001 ]1,',','[ z y x z y x zyx

7 Rotation in 2D • Consider rotation of point (x,y) about the origin by θ degrees in polar coordinates: x = r cos φ y = r sin φ x’ = r cos (φ + θ) = r cos φ cos θ – r sin φ sin θ = x cos θ – y sin θ y’ = r sin (φ + θ) = r sin φ cos θ + r cos φ sin θ = x sin θ + y cos θ

8 Rotation about z axis • Rotation about z axis in 3D leaves all points with the same z coordinate x’ = x cos θ – y sin θ • y’ = x sin θ + y cos θ • z’ = z                         − = 11000 0100 00cossin 00sincos ]1,',','[ z y x zyx θθ θθ

9 Rotation about x axis • Same argument as for rotation about z axis ­ For rotation about x axis, x is unchanged • x’ = x • y’ = y cos θ – z sin θ • z’ = y sin θ + z cos θ                         − = 11000 0cossin0 0sincos0 0001 ]1,',','[ z y x zyx θθ θθ

10 Rotation about y axes • Same argument as for rotation about z axis ­ For rotation about y axis, y is unchanged • x’ = x cos θ + z sin θ • y’ = y • z’ = ­ x sin θ + z cos θ                         − = 11000 0cos0sin 0010 0sin0cos ]1,',','[ z y x zyx θθ θθ

11 Scaling                         = 11000 000 000 000 ]1,',','[ z y x s s s zyx z y x x’=sx x y’=sy y z’=sz z • Expand or contract object along each axis

12 Reflection •corresponds to negative scale factors originalsx = -1 sy = 1 sx = -1 sy = -1 sx = 1 sy = -1

13 Inverses • Although we could compute inverse matrices by general formulas, we can use simple geometric observations ­ Translation: T-1 (dx, dy, dz) = T(­dx, ­dy, ­dz) ­ Rotation: R-1 (θ) = R(-θ) = RT (θ) • Holds for any rotation matrix because cos(-θ) = cos(θ) and sin(-θ)= -sin(θ) ­ Scaling: S-1 (sx, sy, sz) = S(1/sx, 1/sy, 1/sz)

14 Concatenation • We can form arbitrary affine transformation matrices by multiplying together rotation, translation, and scaling matrices • Because the same transformation is applied to many vertices, the cost of forming a matrix M=ABCD is not significant compared to the cost of computing Mp for many vertices p • The difficult part is how to form a desired transformation from the specifications in the application

15 Order of Transformations • Consider the composite transformation matrix M=ABC • When we calculate Mp, matrix C is the first applied, then B, then A • Mathematically, the following are equivalent p’ = ABCp = A(B(Cp)) • Hence composition order really matters!!

16 Rotation About Point P • Move fixed point P to origin • Rotate by desired angle • Move fixed point P back M = T(pf) R(θ) T(-pf)

Thank You ???? 17

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