1. Computational Geometry Piyush Kumar (Lecture 1: Introduction) Welcome to CIS5930

2. Today My Info : Timings for the class References Pre-Requisites How you will be graded Syllabus About Computational Geometry  and its applications Befriend some simple concepts :  Points, Vectors, Affine Spaces, Convexity...  ( Just old wine with new names )

3. Instructor Piyush Kumar 105B Love Building Ph: 850-645-2355 Web page: www.compgeom.com/~piyushwww.compgeom.com/~piyush Email: piyush@acm.org

4. Class Timings To be announced in the first class.  First Class at Love 0301  Wednesday, Jan 5 th (5:15pm – 6:30pm) Final Exam  April 27 th, Wednesday, 5:30 to 7:30pm.

5. References Berg et.al  CG and its applications (2 nd ed) Lecture notes from Dr. Mount Other References  Jirka Matousek’s oLectures on Discrete Geometry  My slides and notes  Rourke’s ‘CG in C’

6. PreReq Algorithms (COP 4530 or higher) C++ Basic Math skills Lot of Time to hack the course.

7. What can you expect? After the course expect to  Know more about geometric algorithms (of course)  Think geometrically  Know how to solve geometric problems oBoth in theory (algorithm) and practice (code)  Be better at applications that require geometric algorithms: oGraphics, Visualization, Game programming, Robotics,… o(and applications you never imagined could use geometry)  Expect to meet some big shots in CG during the course or just afterwards.

8. Grading* Homework : 25% Exam 1 : 25% Programming Assignments: 20% Final Project: 25% Project Presentation: 5% * Modified from original announcement. Theory Real World

9. Syllabus* NN Searching Convexity and Convex hulls Segment intersection, Visibility and Polygon Triangulation Linear Programming and Quadratic Programming  Perceptrons, SVMs and MEBs (ML) Orthogonal Range Searching, Quad Trees and BSP Trees.  Applications to Game Programming. Point Location Voronoi Diagram and Delaunay Triangulations Arrangements and applications Robot Motion Planning Dimension Reduction Popular Demand Topics - ?

10. Computational Geometry What is it about ?  Isnt the name self explanatory?  Its tough to define an entire area which lies in Math ∩ CS. There are always things on the edge, that become central with time.  We’ll move on and learn what we can…

11. What is it good for?

12. © Metris © NASA

13. What kind of problems are you talking about? Nearest Neighbor queries? q p

14. Collision detection © Klosowski, Mitchell

15. Surface Reconstruction

16. Motion Planning How does pioneer 10 move? © NASA Find me a target? © Courtesy Kovan Research Lab

17. Machine Learning Have I seen you before?

18. Geographic Information Systems Courtesy USGS

19. Computational Fluid Dynamics Model of pressure distribution over a CF-18 aircraft Courtesy NRC/CNRC

20. The Beginning