CMPSCI 370: Introduction to Computer Vision
Offering: Spring, 2017
This introductory computer vision class will address fundamental
questions about getting computers to "see" like humans. We
investigate questions such as -- What is the role of vision in
intelligence? How are images represented in a computer? How can we
write algorithms to recognize an object? How can humans and
computers "learn to see better" from experience? We will write a
number of basic computer programs to do things like recognize
handwritten characters, track objects in video, and understand the
structure of images.
The course will introduce a number of key concepts, techniques
and algorithms. The focus will be on the mathematical foundations
rather than the use of software packages as black box. The
course requires appropriate mathematical background in probability
and statistics, calculus, linear algebra. Prior familiarity
with Matlab will be helpful, but not required. Students will be
taught basic programming using Matlab during the course. The
course has the following official prerequisites: CMPSCI 240 or
CMPSCI 383 with a 'C' or better.
- Class hours: Tuesday/Thursday 11:30AM - 12:45PM, LGRT 121
- TA office hours: Chenyun Wu, Monday 2-3PM CS 270
- Instructor office hours: Subhransu Maji, CS 274 (Tuesday after class)
- All the lecture materials, homework assignments, and other resources will be posted on moodle. Registered students can acccess the moodle page here.
- All discussions and annoucements will be posted on piazza. You can sign up for piazza here.
There is no required textbook for this class. The books below are useful references.
We will use the following grading scheme: homework (60%), mid-term (15%), final (25%)
If you need to sign up on the override waitlist, make sure to do it on the CS department's form at: www.cs.umass.edu/overrides
. Make sure to carefully describe your reason to take the course.
- Week 1: Introduction
- Week 2: Pinhole camera model, lenses, sensors
- Week 3: Color perception
- Week 4: Signal quantiaztion, color maps, basic image processing
- Week 5: Edge detection
- Week 6: Corner detection
- Week 7: Image features
- Week 8: Image transformation and feature matching
- Week 9: Recognition basics
- Week 10: Image representations
- Week 11: Intro to machine learning
- Week 12: Convolutional neural networks
- Week 13: Advanced topics
Past offerings at the university
The University is committed to providing an equal educational opportunity for all students. If you have a documented physical, psychological, or learning disability on file with Disability Services (DS), you may be eligible for reasonable academic accommodations to help you succeed in this course. If you have a documented disability that requires an accommodation, please notify me within the first two weeks of the semester so that we may make appropriate arrangements.
Since the integrity of the academic enterprise of any institution of higher education requires honesty in scholarship and research, academic honesty is required of all students. Students are expected to be familiar with this policy and the commonly accepted standards of academic integrity (http://www.umass.edu/honesty