CSC I6716 Computer Vision- Spring 2014
Instructor: Professor Zhigang Zhu
Section: 2TU Code: 3593 Credits: 3.0
Class Meet Time: Tuesdays 7:30 - 10:00 PM , Room: Harris Hall (Rm HR 12)
Office Hours: Tuesdays 3:30 - 5:00 pm , Room: NAC 8/211
City College of New York
Jan 28 (Tuesday), 2014. First class meet of our course.
Feb 10, 2014. Each student please send me your up-to-date resume. We will use this for obtaining your contact information and recommending course projects, and connecting with possible research opportunities, some requiring US Citizens/Permanent Residents. Please add in your research interests and your citizenship.
March 08, 2014, Grading for Assignment 1.
March 10, 2014.
Professor Jeff Bigham from CMU will give a talk on Crowd
Agents: A Top-Down Approach to Truly Intelligent Systems.
You are encouraged to attend this interesting talk, at 12:15 pm
in Room NAC 6/113.
March 17, 2014. Course Project Requirements and Possible Project Topics
March 24, 2014, Grading for Assignments 1 and 2.
Assignment 3 deadline is extended to
April 1, before class.
April 07, 2014, Grading for Assignments 1to 3.
We will discuss Assignment 3 and do a review of the exam in
class on Tuesday April 8.
April 23, 2014. Three important notices: (1) Assignment 4 will be due on April 29, 2014 before class. (2) We will have our exam on April 29, 2014, from 7:30 - 9:10 pm for 100 minutes. (3) ALL students will present for 10 minutes (7 minutes talk + 3 minutes QAs) on May 06, 2014 from 7:30 am - 9:50 pm. Reports will be due before the class on May 15, 2014, when we will discuss Assignment 4, the Exam, and have some make-up presentations.
May 06, 2014. The student presentations will be held in NAC 8/207, the Computer Science Conference Room at the same time, 7:30 - 9:50 pm
May 13, 2014, Grading for Assignment 4 and Exam.
May 15, 2014. The last class will be changed to May 15 (Thursday) in NAC 8/207, the same time 7:30 pm. We will discuss the Exam, projects and homework #4. Reports will be due in class on May 15.
May 25, 2014. Final Grading.
Computer vision has a rich history of fundamental
work on color, stereo and visual motion, which has dealt
with the problems of color image understanding, 3D reconstruction
from multiple images, and structure from motion from video
sequences. Recently, in addition to these traditional problems,
the stereo and motion information presented in multiple images or
a video sequence is also being used to solve several other
interesting problems, for example, large-scale scene modeling and
rendering, video mosaicing, video segmentation, video compression
and transmission, video manipulation, mobile vision, and
first person vision. The best successful vision systems that
computer vision researchers can learn from are human vision
systems. Therefore this course will also briefly discuss human
vision science and explore how the brain sees the world, thus
including introductory on computational neuroscience, motion,
color and several other topics.
(Spring 2014 academic calendar)
Part 0. Introduction and Human Vision
Part I. 2D Computer Vision Basics
I-1. Image Formation: Digital Image Basics (slides)
I-2. Image Enhancement (slides) (Lecture notes on feature extraction:I-2 and I-3) -02/18
I-3. Edge Detection: (slides) (Assignment 2) - 02/25
Part II. 3D Computer Vision
II-1. Camera Models (slides)
notes) - 03/04
II-2. Camera Calibration (slides)
3) - 03/11
(Problem Definition: the Tools You Must Know),
(Direct Approach: Divide and Conquer),
(Projective Matrix Approach: All in One )
II-3. Stereo Vision (slides)
notes ) (Assignment
4) -03/18, 03/25
(Problem Definition & Epipolar Geometry) , Project Discussions
(Correspondence Problem & Reconstruction Problem)
II-4. Visual Motion - (slides)
notes) - 04/01, 04/08
(The Motion Field of Rigid Motion)
(Optical Flow Approach &
Part III. Exam, Projects and Project
III-1. Exam -04/29
III-2. Student Project
Presentations - 05/06
III-3. Project Reports due; Exam and Homework Discussions; Project Make-up Presentations and Discussions 05/13
Online References and additional readings when necessary.
The course will accommodate both graduate and senior undergraduate students with background in computer science, electrical and computer engineering, or applied mathematics. Students who take the course for credits will be required to finish 4 assignments (40%), one midterm exam (40%), and one programming project (20%, including submit a report and give a small presentation to the class at the end of the semester). The topics of the projects will be given in the middle of the semester and will be related to the material presented in the lectures.
Students are required to have a good preparation in both mathematics (linear algebra/numerical analysis) and advanced programming.
Copyright @ Zhigang Zhu , Spring 2014