CS 682 Home |
Homeworks, handouts, lecture notes
This course will
cover basis principles of image formation, different algorithms
for estimating various quantities from single or multiple images
(video). Apllications to vision-based control, 3D
reconstruction, video analysis, surveillance and object recognition
will be discussed.
Syllabus:
1. Representation of 3-D moving scene :
rigid body motion, Euclidean, affine and projective transformations.
2. Image formation: geometric and photometric
aspects of image formation process, grey level and color images
3. Image features and Correspondence:
geometric and photometric features, feature detection and matching,
optical flow
4. Stereo - Two view geometry: camera pose
and 3D structure recovery from two views, camera calibration, 3-D
reconstruction
6. Multiview Geometry: recovery of camera
poses and 3D structure from multiple views, recursive estimation from
motion sequences
8. Grouping and Segmentation: detection and
recovery of multiple motions
9. Detection and Recognition of 0bjects in Images:
object representations and classification methods
10. Selected topics: vision based control,
image based rendering pipeline, vision for human computer intraction,
recognition
Grading: Homeworks (about every 2 weeks)
40% Midterm: 30% Final project: 30%
Prerequisites:linear algebra,
calculus
Lecture Materials: Lecture
notes and slides
Recommended Textbooks:
Required Software:
Matlab