| Instructor: | Eero Simoncelli |
| Time: | Tue 10-12 am |
| Location: |
Meyer Hall, rm 1024 [Take elevator to 10th floor. Phone the "Laboratory for Computational Vision" for access] |
| Prerequisites: | linear algebra, linear systems theory, basic probability/statistics. Some matlab programming experience. |
Brief Description: A graduate-level lecture course on theory and tools for representing, manipulating and analyzing visual images. Topics to include: imaging and optics, multi-scale and differential image decompositions, alignment and displacement estimation, pattern matching, statistical image modeling and its use in compression, estimation, enhancement and synthesis. Course includes extensive Matlab exercises.
| Date | Topic | Handouts/Reading | Homework |
| 8 Sep 10-12am |
Intro / the visual (plenoptic) world / imaging [Lecture slides] |
Course description,
Background poll, Plenoptic chapter |
|
| 15 Sep 10-12pm |
Color representation, Multi-D linear systems [Lecture slides] |
||
| 22 Sep 10-12pm |
Sampling, aliasing | ||
| 29 Sep 10-12pm |
Differentiation of sampled images | Short article on discrete differentiation | |
| 6 Oct 10-12pm |
Orientation estimation, orientation tensors [Lecture slides (last 3 sessions)] |
hw1, due 10/16 shift.m, cconv2.m rconv2.m, localOri.m |
|
| 13 Oct 10-12pm |
Orientation estimation, steerability | ||
| 20 Oct 10-12pm |
Matching: fundamentals for displacement estimation or pattern matching | ||
| 27 Oct 10-12pm |
Coarse-to-fine differential matching | Book chapter | |
| 3 Nov 10-12pm |
Multi-scale representation |