布朗大学视觉课程CS143简介

CS 143 Introduction to Computer Vision

Fall 2013, MWF 1:00 to 1:50, Kasser House, Foxboro Auditorium
Instructor: James Hays

TAs: Hari Narayanan (HTA), Libin "Geoffrey" Sun, Greg Yauney, Bryce Aebi, Charles Yeh, and Kurt Spindler.

Course Description

Course Catalog Entry
How can computers understand the visual world of humans? This course treats vision as a process of inference from noisy and uncertain data and emphasizes probabilistic, statistical, data-driven approaches. Topics include image processing; segmentation, grouping, and boundary detection; recognition and detection; motion estimation and structure from motion. This offering of CS 143 will emphasize the core vision tasks ofscene understanding and recognition. We will train and evaluate classifiers to recognize various visual phenomena.

The course will consist of five programming projects and two written quizzes. This course satisfies the graduate A.I area requirement.

Prerequisites

This course requires programming experience as well as linear algebra, basic calculus, and basic probability. Previous knowledge of visual computing will be helpful. The following courses (or equivalent courses at other institutions) are helpful prerequisites:

• CS 123, Introduction to Computer Graphics
• CS 129, Computational Photography
• CS 195-F, Introduction to Machine Learning

Some of the course topics overlap with these related courses, but none of the assignments will.

Assignments

Winning projects

All Results

Image Filtering and Hybrid imagesYipin Zhou,Tuo Shao,Sarah ParkerProject 1 resultsLocal Feature MatchingTuo Shao,Junzhe Xu,Patsorn SangkloyProject 2 resultsScene Recognition with Bag of WordsChun-Che Wang,Patsorn Sangkloy,
Junzhe Xu,Michael WangProject 3 resultsFace Detection with a Sliding WindowJake Ellis,Jincheng Li,
Patsorn Sangkloy,Yipin Zhou,Project 4 resultsBoundary Detection with Sketch TokensJunzhe Xu,Sonia Phene, Chun-Che Wang,
Valay Shah,Yun MiaoProject 5 resultsIt is strongly recommended that all projects be completed in Matlab. All starter code will be provided for Matlab. Students may implement projects through other means but it will generally be more difficult.

Textbook

Readings will be assigned in "Computer Vision: Algorithms and Applications" by Richard Szeliski. The book is available for free online or available for purchase.

Grading

Your final grade will be made up from

• 80% 5 programming projects
• 20% 2 written quizzes

You will lose 10% each day for late projects. However, you have three "late days" for the whole course. That is to say, the first 24 hours after the due date and time counts as 1 day, up to 48 hours is two and 72 for the third late day. This will not be reflected in the initial grade reports for your assignment, but they will be factored in and distributed at the end of the semester so that you get the most points possible.

Important Links: