The goal of computer vision is to compute properties of the three-dimensional
world from digital images. Problems in this field include identifying the 3D
shape of an environment, determining how things are moving, and recognizing
familiar people and objects, all through analysis of images and video. This
course provides an introduction to computer vision, including such topics as
feature detection, image segmentation, motion estimation, image mosaics, 3D
shape reconstruction, and object recognition.
Notes about office hours: If it's impossible for you to
make it to scheduled office hours, you can usually arrange an appointment with
the TA or instructor. Just send an email requesting a meeting.
Prerequisites
- Data structures
- A good working knowledge of C and C++ programming
- Linear algebra
- Vector calculus
- No prior knowledge of vision is assumed.
Textbooks
CSE 455 Course Reader, available in the
in reader, at UW Bookstore in the CSE textbook area.
Click here for pricing.
Administrative
Grading
- Programming Projects (70%)
- Midterm (15%)
- Final (15%)
- Late projects will be penalized by 33% for each day it is late, and
no extra credit will be awarded. A project due on Friday morning that
is turned in on Monday night or Tuesday morning will count two days late
(weekends do not count).
Syllabus (tentative)
- Image Processing (2 weeks)
- filtering, convolution
- image pyramids
- edge detection
- features
- hough transform
- Image Transformation (2 weeks)
- image warping (parametric transformations, resampling, 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
- 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)
Last modified 1/3/2012