1. Geometry CSC 2141 Introduction to Computer Graphics

2. Objectives  Basic geometric problems are fundamental to computer graphics, and we will present tools to answer these sorts of questions  Geometric intersections  Transformation  Change of coordinates  Introduce the elements of geometry  Scalars  Vectors  Points  Develop mathematical operations among them in a coordinate-free manner

3. Basic Elements  Geometry is the study of the relationships among objects in an n- dimensional space  In computer graphics, we are interested in objects that exist in three dimensions  We will need three fundamental types  Scalars  Vectors  Points

4. Coordinate-Free Geometry  When we learned simple geometry, most of us started with a Cartesian approach  Points were at locations in space p=(x,y,z)  We derived results by algebraic manipulations involving these coordinates  This approach was nonphysical  Physically, points exist regardless of the location of an arbitrary coordinate system  Most geometric results are independent of the coordinate system  Example Euclidean geometry: two triangles are identical if two corresponding sides and the angle between them are identical

5. Scalars  Scalars can be defined as members of sets which can be combined by two operations (addition and multiplication) obeying some fundamental axioms (associativity, commutivity)  Examples include the real and complex number systems under the ordinary rules with which we are familiar  Scalars alone have no geometric properties

6. Vectors  Physical definition: a vector is a quantity with two attributes  Direction  Magnitude  Examples include  Force  Velocity  Directed line segments = vector  Most important example for graphics v

7. Vector Operations  Every vector has an inverse  Same magnitude but points in opposite direction  Every vector can be multiplied by a scalar changing its magnitude  There is a zero vector  Zero magnitude, undefined orientation  The sum of any two vectors is a vector  Use head-to-tail axiom  Subtraction of vectors: v-u = v + (-u) v -v vv v u w

8. Linear Vector Spaces  Mathematical system for manipulating vectors  Involve only scalars and vectors  Combine scalars and vectors to form new ones  Operations  Scalar-vector multiplication u =  v  Vector-vector addition: w = u + v  Expressions such as v=u+2w-3r Make sense in a vector space

9. Vectors Lack Position  These vectors are identical  Same length and magnitude  “free vectors”  Vector spaces insufficient for geometry  Need points

10. Points  Location in space  Operations allowed between points and vectors  Point-point subtraction yields a vector  Equivalent to point-vector addition P=v+Q v=P-Q Directed from P to Q Is defined to be translation of Q by displacement v

11. Affine Spaces  Point + a vector space  Manipulates scalars, vectors and points  Operations  Vector-vector addition (vector-vector subtraction)  Scalar-vector multiplication (vector-scalar division)  Point-vector addition (point-vector subtraction)  Point-point subtraction  Scalar-scalar operations  For any point define  1 P = P  0 P = 0 (zero vector)

12. Lines  Consider all points of the form  P(  )=P 0 +  d  Set of all points that pass through P 0 in the direction of the vector d  Called “parametric form”  Line: infinitely long in both directions

13. Rays and Line Segments  If  >= 0, then P(  ) is the ray leaving P 0 in the direction d  If we use two points to define v, then P(  ) = Q +  (R-Q)=Q+  v =  R + (1-  )Q For 0<=  <=1 we get all the points on the line segment joining R and Q  Ray: infinitely long in one direction  Line segment: finite

14. Affine and Convex Sums (combinations)  In general, we define the following two operations for points in affine space.  Consider the “sum” P=  1 P 1 +  2 P 2 +…..+  n P n  This sum makes sense iff  1 +  2 +…..  n =1 in which case we have the affine sum of the points P 1  P 2,…..P n  If, in addition,  i >=0, we have the convex sum (combination) of P 1  P 2,…..P n

15. Planes  A plane can be defined by a point and two vectors or by three points P( ,  )=R+  u+  v P( ,  )=R+  (Q-R)+  (P-Q) u v R P R Q

16. Triangles convex sum of P and Q convex sum of S(  ) and R for 0<= ,  <=1, we get all points in triangle

17. Normals  Every plane has a vector n normal (perpendicular, orthogonal) to it  From point-two vector form P( ,  )=R+  u+  v, we know we can use the cross product to find n = u  v  and the plane equation is (P(  )-P)  n=0 u v P