1. Computational Geometry The systematic study of algorithms and data structures for geometric objects, with a focus on exact algorithms that are asymptotically fast. Two key ingredients of a good algorithmic solution:  Thorough understanding of the problem geometry.  Proper application of algorithmic techniques and data structures.

2. Example 1  Proximity Closest café on campus? Voronoi diagram Delaunay triangulation

3. Example 2  Path Planning Robot How can a robot find a short route to the destination that avoids all obstacles?

4. Applications in Computer Graphics Creating scene images on a display device.  Intersect geometric primitives (lines, polygons, polyhedra, etc.)  Determine primitives lying in a region.  Hidden surface removal – determine the visible part of a 3D scene while discard the occluded part from a view point.  Create realistic-looking scenes – taking into account lighting and computing shadows.  Deal with moving objects and detect collisions.

5. Applications in Robotics How the robot perceives, understands, and acts upon its environment,  Motion planning.  Grasping.  Parts orienting.  Optimal placement.

6. Applications in GIS Storage of geographical data (contours of countries, height of mountains, course of rivers, population, roads, electricity lines, etc.)  Large amount of data – requiring efficient algorithms.  Geographic data storage (e.g., map of roads for car positioning or computer display).  Interpolation between nearby sample data points  Overlay of multiple maps.

7. Applications in CAD/CAM Design of Products with a computer.  Intersection, union, and decomposition of objects.  Testing on product specifications.  Design for assembly – modeling and simulation of assembly.  Testing design for feasibility.

8. Line Segments & Vectors p = (x, y ) 1 2 O = (0, 0)x y 1 2 Points (vectors): p, p, p  p = p p 1 2 1 2 2 1 p  p = (x  x, y  y ) 1 2 Line segment: p p = p p 2 1 1 2

9. Dot (Inner) Product x y (0, 0) p p 1 2 p  p = x x + y y = p  p = |p | |p | cos  1 2 1 2 1 2 2 1 1 2 

10. Cross (Vector) Product x y (0, 0) p p 1 p + p 1 2 2 p  p is the signed area of the parallelogram. 1 2 p  p = x y  x y =  p  p = |p | |p | sin  1 2 1 2 2 1 2 1 1 2  p and p are collinear iff p  p = 0. 1 2 1 2

11. Turning of Consecutive Segments Counterclockwise Clockwise No turn (collinear) p p p 0 1 2 p p p 0 1 2 pp p 0 12 p p  p p > 0 0 1 0 2 p p  p p < 0 0 1 0 2 p p  p p = 0 0 1 0 2 Segments p p and p p. Move from p to p then to p. 0 1 1 2 0 1 2

12. Intersection of Two Lines p Rewrite the above equations in terms of dot products: Hence is perpendicular to both and. must be parallel to their cross product!

13. Homogeneous Coordinates Represent every point as homogeneous coordinates of Intersection is parallel to the cross product vector: Normalize the z-coordinate of the cross product to 1. Hence the intersection point: homogeneous coordinates of intersection

14. Intersection Example Find the intersect point of the lines: Take the cross product of the two coefficient vectors: Intersection point:

15. Two Parallel Lines point at infinity Two parallel lines “intersect” at infinity.

16. Line through Two Points Scaling yields the same line! Ex. The line through (3, 1) and (-4, 5) has coefficients (i.e., homogeneous coordinates) and equation

17. Advantages of Homogeneous Coordinates Scaling independent: Uniform handling of all cases (horizontal, perpendicular, parallel lines, etc.) No need to solve equations – just take a cross product. all represent the same point