16-385 Computer Vision, Spring 2018
|Time:||Mondays, Wednesdays 1:30PM - 2:50PM|
|Location:||Doherty Hall 1112|
|Instructor:||Ioannis (Yannis) Gkioulekas|
|Teaching Assistants:||Gaurav Mittal, Shashank Tripathi|
This course provides a comprehensive introduction to computer vision. Major topics include image processing, detection and recognition, geometry-based and physics-based vision and video analysis. Students will learn basic concepts of computer vision as well as hands on experience to solve real-life vision problems.
This course requires familarity with linear algebra, calculus, basic probability, as well as programming. In particular, the following courses serve as prerequisite:
Matlab will be used for project assignments and will be covered as part of the introduction to the course.
Readings will be assigned from the following textbook (available online for free):
Additional readings will be assigned from relevant papers. Readings will be posted at the last slide of each lecture.
The following textbooks can also be useful references but are not required:
Your final grade will be made up from:
Homework assignments: All homework assignments will have a programming component, and some of them will also have a theory component involving pen-and-paper exercises. The programming component of all assignments be done in Matlab. There will be an ungraded zeroth assignment that will serve as a short Matlab tutorial. We have collected a few useful Matlab resources here.
Late days: For the homework assignments, students will be allowed a total of three free late days. Any additional late days will each incur a 10% penalty.
Submitting homeworks: We use Canvas for submitting and grading homeworks.
We use Piazza for class discussion and announcements.
Email: Please use  in the title when emailing the teaching staff!
Office hours: Regular office hours will be as shown below.
Feel free to email us about scheduling additional office hours.
Discussion: We use Piazza for class discussion and announcements.
The following syllabus is tentative and will most likely change during the semester. Slides will be updated on this site after each lecture.
|W, Jan 17||Introduction||pdf, pptx|
|M, Jan 22||Image filtering||pdf, pptx|
|W, Jan 24||Image pyramids and Fourier transform||pdf1/pdf2, pptx/pptx2||HW0 and HW1 out|
|M, Jan 29||Hough transform||pdf, pptx|
|W, Jan 31||Feature and corner detection||pdf, pptx|
|M, Feb 5||Feature descriptors and matching||pdf, pptx|
|W, Feb 7||2D transformations||pdf, pptx||HW1 due|
|F, Feb 9||HW2 out|
|M, Feb 12||Image homographies||pdf, pptx|
|W, Feb 14||Camera models||pdf, pptx|
|M, Feb 19||Two-view geometry||pdf, pptx|
|W, Feb 21||Stereo||pdf, pptx|
|F, Feb 23||HW2 due, HW3 out|
|M, Feb 26||Structure from motion||pdf, pptx|
|W, Feb 28||No class|
|M, Mar 5||Radiometry and reflectance||pdf, pptx|
|W, Mar 5||Photometric stereo and shape from shading||pdf, pptx|
|F, Mar 9||HW3 due, HW4 out|
|M, Mar 12||No class (spring break)|
|W, Mar 14||No class (spring break)|
|M, Mar 19||Color||pdf, pptx|
|W, Mar 21||Image processing pipeline||pdf, pptx|
|F, Mar 23||HW4 due, HW5 out|
|M, Mar 26||Introduction to recognition||pdf, pptx|
|W, Mar 28||Bag of words||pdf, pptx|
|M, Apr 2||Neural networks||pdf, pptx|
|W, Apr 4||Convolutional neural networks||pdf, pptx|
|F, Apr 6||HW5 due, HW6 out|
|M, Apr 9||Faces||pdf, pptx|
|W, Apr 11||Optical flow||pdf, pptx|
|M, Apr 16||Alignment||pdf, pptx|
|W, Apr 18||Tracking||pdf, pptx|
|F, Apr 20||HW6 due, HW7 out|
|M, Apr 23||Temporal models and SLAM||pdf, pptx|
|W, Apr 25||Graph-based methods||pdf, pptx|
|M, Apr 30||Segmentation||pdf, pptx|
|W, May 2||Wrap-up and discussion||pdf, pptx|
|S, May 6||HW7 due|
These lecture notes have been pieced together from many different people and places. Special thanks to colleagues for sharing their slides: Kris Kitani, Bob Collins, Srinivasa Narashiman, Martial Hebert, Alyosha Efros, Ali Faharadi, Deva Ramanan, Yaser Sheikh, and Todd Zickler. Many thanks also to the following people for making their lecture notes and materials available online: Steve Seitz, Richard Selinsky, Larry Zitnick, Noah Snavely, Lana Lazebnik, Kristen Grauman, Yung-Yu Chuang, Tinne Tuytelaars, Fei-Fei Li, Antonio Torralba, Rob Fergus, David Claus, and Dan Jurafsky.