1. University of British Columbia CPSC 314 Computer Graphics Jan-Apr 2005 Tamara Munzner http://www.ugrad.cs.ubc.ca/~cs314/Vjan2005 Math Review Week 1, Fri Jan 7

2. 2 News graphics-related distinguished lecture Frontiers in 3D Photography seminar Steven Seitz, University of Washington Thursday, January 13, 4:00 pm Dempster, room TBA aimed at a broad audience extra handouts left in CICSR 011 lab, by whiteboard

3. 3 Reading FCG Chapter 2: Miscellaneous Math except for 2.11 (covered later) skim 2.2 (sets and maps), 2.3 (quadratic eqns) important: 2.3 (trig), 2.4 (vectors), 2.5-6 (lines) 2.10 (linear interpolation) skip 2.5.1, 2.5.3, 2.7.1, 2.7.3, 2.8, 2.9 FCG Chapter 4.1-4.25: Linear Algebra skim 4.1 (determinants) important: 4.2.1-4.2.2, 4.2.5 (matrices) skip 4.2.3-4, 4.2.6-7 (matrix numerical analysis)

4. 4 Textbook Errata list at http://www.cs.utah.edu/~shirley/fcg/errata http://www.cs.utah.edu/~shirley/fcg/errata p 29, 32, 39 have potential to confuse

5. 5 Notation: Scalars, Vectors, Matrices scalar (lower case, italic) vector (lower case, bold) matrix (upper case, bold)

6. 6 Vectors arrow: length and direction oriented segment in nD space offset / displacement location if given origin

7. 7 Column vs. Row Vectors row vectors column vectors switch back and forth with transpose

8. 8 Vector-Vector Addition add: vector + vector = vector parallelogram rule tail to head, complete the triangle geometricalgebraic examples:

9. 9 Vector-Vector Subtraction subtract: vector - vector = vector

10. 10 Vector-Vector Subtraction subtract: vector - vector = vector argument reversal

11. 11 Scalar-Vector Multiplication multiply: scalar * vector = vector vector is scaled

12. 12 Vector-Vector Multiplication multiply: vector * vector = scalar dot product, aka inner product

13. 13 Vector-Vector Multiplication multiply: vector * vector = scalar dot product, aka inner product geometric interpretation lengths, angles can find angle between two vectors

14. 14 Dot Product Geometry can find length of projection of u onto v as lines become perpendicular,

15. 15 Dot Product Example

16. 16 Vector-Vector Multiplication, The Sequel multiply: vector * vector = vector cross product algebraic geometric parallelogram area perpendicular to parallelogram

17. 17 RHS vs LHS Coordinate Systems right-handed coordinate system left-handed coordinate system right hand rule: index finger x, second finger y; right thumb points up left hand rule: index finger x, second finger y; left thumb points down convention

18. 18 Basis Vectors take any two vectors that are linearly independent (nonzero and nonparallel) can use linear combination of these to define any other vector:

19. 19 Orthonormal Basis Vectors if basis vectors are orthonormal (orthogonal (mutually perpendicular) and unit length) we have Cartesian coordinate system familiar Pythagorean definition of distance orthonormal algebraic properties

20. 20 Basis Vectors and Origins coordinate system: just basis vectors can only specify offset: vectors coordinate frame: basis vectors and origin can specify location as well as offset: points

21. 21 Working with Frames F1F1F1F1 F1F1F1F1

22. 22 Working with Frames F1F1F1F1 F1F1F1F1 p = (3,-1)

23. 23 Working with Frames F1F1F1F1 F1F1F1F1 p = (3,-1) F2F2F2F2 F2F2F2F2

24. 24 Working with Frames F1F1F1F1 F1F1F1F1 p = (3,-1) F2F2F2F2 p = (-1.5,2) F2F2F2F2

25. 25 Working with Frames F1F1F1F1 F1F1F1F1 p = (3,-1) F2F2F2F2 p = (-1.5,2) F3F3F3F3 F2F2F2F2 F3F3F3F3

26. 26 Working with Frames F1F1F1F1 F1F1F1F1 p = (3,-1) F2F2F2F2 p = (-1.5,2) F3F3F3F3 p = (1,2) F2F2F2F2 F3F3F3F3

27. 27 Named Coordinate Frames origin and basis vectors pick canonical frame of reference then don’t have to store origin, basis vectors just convention: Cartesian orthonormal one on previous slide handy to specify others as needed airplane nose, looking over your shoulder,... really common ones given names in CG object, world, camera, screen,...

28. 28 Lines slope-intercept form y = mx + b implicit form y – mx – b = 0 Ax + By + C = 0 f(x,y) = 0

29. 29 Implicit Functions find where function is 0 plug in (x,y), check if 0: on line < 0: inside > 0: outside analogy: terrain sea level: f=0 altitude: function value topo map: equal-value contours (level sets)

30. 30 Implicit Circles circle is points (x,y) where f(x,y) = 0 points p on circle have property that vector from c to p dotted with itself has value r 2 points points p on the circle have property that squared distance from c to p is r 2 points p on circle are those a distance r from center point c

31. 31 Parametric Curves parameter: index that changes continuously (x,y): point on curve t: parameter vector form

32. 32 2D Parametric Lines start at point p 0, go towards p 1, according to parameter t p(0) = p 0, p(1) = p 1

33. 33 Linear Interpolation parametric line is example of general concept interpolation p goes through a at t = 0 p goes through b at t = 1 linear weights t, (1-t) are linear polynomials in t

34. 34 Matrix-Matrix Addition add: matrix + matrix = matrix example

35. 35 Scalar-Matrix Multiplication multiply: scalar * matrix = matrix example

36. 36 Matrix-Matrix Multiplication row by column

37. 37 Matrix-Matrix Multiplication row by column

38. 38 Matrix-Matrix Multiplication row by column

39. 39 Matrix-Matrix Multiplication row by column

40. 40 Matrix-Matrix Multiplication row by column noncommutative: AB != BA

41. 41 Matrix Multiplication can only multiply if number of left cols = number of right rows legal undefined

42. 42 Matrix-Vector Multiplication points as column vectors: postmultiply points as row vectors: premultiply

43. 43 Matrices transpose identity inverse not all matrices are invertible

44. 44 Matrices and Linear Systems linear system of n equations, n unknowns matrix form Ax=b