Computer Vision Fall 2005

CSC I6716 Computer Vision- Fall 2005

Time: Tuesday 04:30-07:00 PM
Room: SH-276
Credits: 3.0
Office Hours: Tuesday 1:30 - 4:00 pm

Course Update Information

Aug 30, 2005. Course Syllabus (with links to slides in Lectures 1 & 2) and Course Requirements online.
Sep 06, 2005. Homework 1 online
Sep 13, 2005. Homework 2 online
Oct 12, 2005. For homework requirements, please click the relate links to see details. When you send your submissions, please do put the Assignment Number in your Subject field of your email.
Oct 15, 2005. Grading for Homework 1
Oct 24, 2005. Homework 3 online
Oct 26, 2005. Grading for Homework 2
Oct 26, 2005. CVVC_Part2_Stereo with classroom notes
Nov 26, 2005, Final project presentations, SH-276 ,TUESDAY DEC 20 @ 4:00-7:00 PM
Nov 30, 2005. Grading for Homework 3 and Midterm Exam . We are going to discuss Exam questions in class on Dec 06. For those of you who have not sent me your work for assignment 3, please bring in your work in HARD copies. You may also show me the programming part of your assignment 3.
Dec 20, 2005, Final project presentations rescheduled (link to your time slots), SH-276 ,TUESDAY Jan 10 @ 4:00-7:00 PM

Dec 13, 2006. Final Grading

Course Objectives

Computer vision has a rich history of work on stereo and visual motion, which has dealt with the problems of 3D reconstruction from multiple images, and structure from motion from video sequences. Recently, in addition to these traditional problems, the stereo and motion information present in multiple images or a video sequence is also being used to solve several other problems, for instance video mosaicing, video synthesis, video segmentation, video compression, video registration, and video surveillance an monitoring. This is summarized as Video Computing. Computer vision is playing an important and somewhat different role in solving these problems in video computing than the original image analysis considered in the early days of vision research.

The course "Computer Vision" will include advanced topics in video computing as well as fundamentals in stereo and motion. The topics will be divided into three parts:

Computer Vision Basics - Introduction, Sensors, Image Formations, Feature Extraction
3D Computer Vision - Camera Models, Camera Calibration, Stereo Vision, Visual Motion
Video Computing - Video Mosaicing, Stereo panoramas, Motion Segmentation and Human Tracking, Image-Based Rendering, Content-Based Video Coding (MPEG4/7)

Note: In addition to attending regular course lectures, students may also be arranged (if appropriate) to attend seminars of the CCNY Lecture Series on Computer Vision, Robotics and Human-Computer Interaction hosted by Prof. Zhu. Students will have opportunities to talk with leading researchers in the fields of computer vision and HCI.

Course Syllabus

Part I. Computer Vision Basics

Topic I-1. Introduction: Image, Vision and 3D Vision (slides) - Aug 30
Topic I-2. Visual Sensors (slides) -Aug 30
Topic I-3. Image Formation and Processing (slides) (Homework 1) - Sep 06
Topic I-4. Features and Feature Extraction (part 1, part 2) (Homework 2) - Sep 13

Part II. 3D Computer Vision

Topic II-1. Camera Models (slides)- Sep 20
Topic II-2. Omnidirectional Cameras (slides) - Sep 27

Discussion 1: Discussions of Homework Assignments - Sep 27

Topic II-3. Camera Calibration (slides)- Oct 18
Topic II-4. Stereo Vision (slides) ( Homework 3) - Oct 25 (slides with online notes)

Discussion 2. Research Experiences in Computer Vision - Nov 1
(1) Multimedia Integration in a Classroom Application by Weihong Li
(2) 3D and Motion Extraction Using a Singel Video Camera by Hao Tang
(3) Omnidirectional Vision and Robot Coordination by Yi Feng

Topic II-5. Visual Motion (slides) - Nov 8

Part III. Video Computing

Topic III-1. Video Mosaicing and Image-Based Rendering - Nov 15

Discussion 3. Reviews and Project Topics - Nov 15

Midterm Exam - Nov 22

Project Designs & Implementations - Nov 29 (No class meet)

Discussion 3. Exam Discussions & Project QAs - Dec 06

Topic III-2. Omnidirectional Stereo (lecture), Student Presentations (???) - Dec 13

Student Project Presentations - SH-276 ,TUESDAY DEC 20 @ 4:00-7:00 PM

Textbook and References

Textbook:
“Introductory Techniques for 3-D Computer Vision”, Trucco and Verri, 1998.

References:

“Computer Vision – A Modern Approach” Forsyth and Ponce, 2003.
“Three Dimensional Computer Vision: A Geometric Viewpoint” O. Faugeras
“Image Processing, Analysis and Machine Vision” Sonika, Hlavac and Boyle, 1999

Supplements: Online References and additional readings when necessary.

Grading and Prerequisites

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 3 assignments of paperwork (30%), one midterm exam (40%), and one programming project with exit interview (30%, 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.

This course will be counted for both "Intelligent Systems" and "Scientific and Statistical Computing Computer Science" Groups for graduate students, and for both "Computational Techniques for Science and Engineering" and "Net-Centric Computing" Electives for undergraduate students.