1	Computer Vision (CSE/EE 576) Staff Prof: Steve Seitz (seitz@cs) TA: Aseem Agarwala (aseem@cs) Web Page http://www.cs.washington.edu/education/courses/cse576/03sp/ Handouts intro lecture filter lecture signup sheet account forms
2	Today Overview of Computer Vision Overview of Course Images & transformations Readings for this week Forsyth & Ponce textbook, chapter 7 Intelligent Scissors http://www.cs.washington.edu/education/courses/576/03sp/readings/mort-sigg95.pdf
3	Every picture tells a story Goal of computer vision is to write computer programs that can interpret images
4	Can computers match human perception? Not yet computer vision is still no match for human perception but catching up, particularly in certain areas
5	Perception
6	Perception
7	Perception
8	Low level processing Low level operations Image enhancement, feature detection, region segmentation
9	Mid level processing Mid level operations 3D shape reconstruction, motion estimation
10	High level processing High level operations Recognition of people, places, events
11	Application: Document Analysis
12	Applications: 3D Scanning
13	Applications: Motion Capture, Games
14	Application: Medical Imaging
15	Applications: Robotics
16	Project 1: Intelligent Scissors
17	Project 2: Panorama Stitching http://www.cs.washington.edu/homes/allen/cse590ss/fridge-big.html
18	Project 3: Face Recognition
19	Project 4 Open-ended research project
20	Class Webpage http://www.cs.washington.edu/education/courses/cse455/03wi/
21	Grading Programming Projects image scissors panoramas face recognition final project one or two written homeworks no final
22	General Comments Prerequisites—these are essential! Data structures A good working knowledge of C and C++ programming Linear algebra Vector calculus Course does not assume prior imaging experience computer vision, image processing, graphics, etc. Emphasis on programming projects!