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CS 3388 Working with 3D Vectors

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1 CS 3388 Working with 3D Vectors
[Hill §4.1—4.4] x z y (1,2,0) (1,2,2) TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: AAAAAAA

2 Vector Spaces The space Rn is a vector space because it is closed under Setting n=3 is special case vector addition: u,v 2 Rn ) u + v 2 Rn scalar multiplication: v 2 Rn, ® 2 R ) ®v 2 Rn

3 k-Flats and Subspaces A subspace is a subset of points
A k-flat is a subspace “congruent” to a vector space of dimension k A point is a 0-flat A line is a 1-flat A plane is a 2-flat y u v z x u

4 Vector Norm Identities: (triangle inequality)

5 3D Dot Product Also known as inner- or scalar product since Notice
If assume (column vectors)

6 Dot Product Identities: Geometry: x z y b a Therefore…

7 Dot Product as Projection
The value is the length of a projected onto b multiplied by If then a b a b

8 Sign of Dot Product If then a and b facing similar directions
If then a and b facing opposite directions Useful for detecting front-facing and back-facing surfaces (much later a

9 Cross Product Also called vector product, as Way to remember order:
(2£2 determinants) careful!

10 Geometry of Cross Product
The vector where If and then If then “c has unit norm” “c orthogonal to a and to b” x z y b a c

11 Cross Product Identities
these follow from

12 Normal Vectors Let be a surface (dimension 2)
For each surface point define A normal at is any such that for all n v p q p

13 Normals for Planes For a plane (2-flat), point doesn’t matter because
Given with can compute a normal Can calculate u,v from non-colinear points x z y n u v (vectors tangential to plane do not change with position) y q p r z x

14 (i.e. do it on blackboard)
Calculating a Normal Let define a plane y q p r z x “Calculemus!” ---Leibniz (i.e. do it on blackboard) y n z x


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