CSC I6716 Computer Vision- Spring 2015
Instructor: Professor Zhigang Zhu
Section: 2TU Code: 54272 Credits: 3.0
Class Meet Time: Tuesdays 7:30 -
10:00 PM , Room: NAC 7/227
Office Hours: Tuesdays 2:30 pm - 4:30 pm, Room: NAC 8/211
City College of New York
Feb 03 (Tuesday), 2015. First class meet of
Feb 17, 2015, Assignment 1 online, Due March 03, 2015.
Feb 18. Office hours changed to 2:30 pm - 4:30 pm.
March 16, 2015, Grading for Assignment 1.
March 17, 2015, Assignment 2 submission deadline extended to March 24, 2015.
March 17, 2015. Assignment 3 submission deadline extended to April 14, 2015 (due to the Spring Break).
March 24, 2015. Assignment 4 online; submission deadline April 28, 2015.
March 24, 2015. Possible Project topics can be found here. Your project topics and teams (1-2 members) will be finalized on April 14 in class , please send in your choices by April 7 (Tuesday).
March 30, 2015,
Grading for Assignments 1 and 2.
April 28, 2015. Exam will be taken during the class meet time, from 7:30 - 9:10 pm for 100 minutes. We will have 20 multiple choice questions and 4 questions for short answers.
April 28, 2015, Grading for Assignments 1 to 3.
April 30, 2015. Project Presentation Schedules for May 05 and May 12, 2015.
May 07, 2015, Grading for Assignments 1 to 3 and Exam. Assignment 4 submission deadline is May 07 at middle night. No submissions will be accepted after that.
May 11, 2015, Grading for Assignments 1 to 4 and Exam. The grading is final and no updated submissions will be accepted.
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 2015 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) -02/17, 02/24
I-3. Edge Detection: (slides) (Assignment 2) - 02/24
Part II. 3D Computer Vision
II-0. Panoramic Stereo Imaging (slides)
- stereo vision from a motion camera (by Edgardo Molina) - 03/03
II-1. Camera Models (slides) (lecture notes) - 03/10
II-2. Camera Calibration (slides) (lecture notes) (Assignment 3) - 03/17
(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) -03/24, 03/31
(Problem Definition & Epipolar Geometry) , Project Discussions
(Correspondence Problem & Reconstruction Problem)
II-4. Visual Motion - (slides) (lecture notes) - 04/14, 04/21
(The Motion Field of Rigid Motion)
(Optical Flow Approach &
& Exam Review
Part III. Exam, Projects and Project
III-1. Exam -04/28
III-2. Student Project
Presentations - 05/05
III-3. Project Reports due; Exam and Homework Discussions; Project Make-up Presentations and Discussions 05/12
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 2015