Computer Vision (CSE P576)
Staff
Prof:  Steve Seitz (seitz@cs )
TA:  Jiun-Hung Chen (jhchen@cs)
Web Page
http://www.cs.washington.edu/education/courses/csep576/05wi/
Handouts
signup sheet
intro slides
image filtering slides
image sampling slides

Today
Intros
Computer vision overview
Course overview
Image processing
Readings for this week
Forsyth & Ponce textbook, chapter 7

Every picture tells a story
Goal of computer vision is to write computer programs that can interpret images

Can computers match human perception?
Yes and no (but mostly no!)
humans are much better at “hard” things
computers can be better at “easy” things

Perception

Perception

Perception

Low level processing
Low level operations
Image enhancement, feature detection, region segmentation

Mid level processing
Mid level operations
3D shape reconstruction, motion estimation

High level processing
High level operations
Recognition of people, places, events

Image Enhancement

Image Enhancement

Image Enhancement

Application:  Document Analysis

Applications:  3D Scanning

Slide 16

Slide 17

Slide 18

Slide 19

Slide 20

Slide 21

Slide 22

Applications:  Motion Capture, Games

Slide 24

Application:  Medical Imaging

Applications:  Robotics

Syllabus
Image Processing (2 weeks)
filtering, convolution
image pyramids
edge detection
feature detection (corners, lines)
hough transform
Image Transformation (2 weeks)
image warping (parametric transformations, texture mapping)
image compositing (alpha blending, color mosaics)
segmentation and matting (snakes, scissors)
Motion Estimation (1 week)
optical flow
image alignment
image mosaics
feature tracking

Syllabus
Light (1 week)
physics of light
color
reflection
shading
shape from shading
photometric stereo
3D Modeling (3 weeks)
projective geometry
camera modeling
single view metrology
camera calibration
stereo
Object Recognition and Applications (1 week)
eigenfaces
applications (graphics, robotics)

Project 1:  Intelligent Scissors

Project 2:  Panorama Stitching
http://www.cs.washington.edu/education/courses/455/03wi/projects/project2/artifacts/crosetti/index.shtml

Project 3:  3D Shape Reconstruction

Project 4:  Face Recognition

Class Webpage
http://www.cs.washington.edu/education/courses/csep576/05wi/

Grading
Programming Projects (100%)
image scissors
panoramas
3D shape modeling
face recognition

General Comments
Prerequisites—these are essential!
Data structures
A good working knowledge of C and C++ programming
(or willingness/time to pick it up quickly!)
Linear algebra
Vector calculus
Course does not assume prior imaging experience
computer vision, image processing, graphics, etc.