Course Meeting Times
Lectures: 2 sessions / wk; 1.5 hrs / session
Prerequisites
6.003 Signal Processing or permission of the instructor.
Course Description
This course focuses on machine vision. Topics include:
- Deriving a symbolic description of the environment from an image.
- Understanding physics of image formation.
- Image analysis as an inversion problem.
- Binary image processing and filtering of images as preprocessing steps.
- Recovering shape, lightness, orientation, and motion.
- Using constraints to reduce the ambiguity.
- Photometric stereo and extended Gaussian sphere.
- Applications to robotics; intelligent interaction of machines with their environment.
Students taking the graduate version complete different assignments.
Grading
Undergraduate 6.801 Grading
| Activities | Percentages |
|---|---|
| Homework | 50% |
| Quiz 1 | 31.5% |
| Quiz 2 | 13.5% |
| Nanoquizzes | 5% |
Graduate 6.868 Grading
| Activities | Percentages |
|---|---|
| Homework | 33% |
| Take-Home Quizzes | 28% (Higher of Quiz 1 and Quiz 2) |
| Final Project | 33% |
| Nanoquizzes | 6% |
There is no final exam. There will be 5 problem sets and 2 take-home quizzes, which are just like problem sets, only longer, and worth more points.
Our goal with nanoquizzes is not to cause undue and unnecessary stress to the students, especially during a pandemic. We believe nanoquizzes are a good way to help students stay up-to-date with the material. When we determine final grades, we will ensure that nanoquizzes can only help your grade, and not bring it down. For instance, nanoquizzes will never bring your grade from an A to a B, but could potentially bring your grade from a B to an A.
