| Time/Place: | TR, 9:30am - 10:48pm, DL 317 |
| Instructor: | Prof. Jim Davis, Office: DL491, Email: jwdavis@cse |
| Grader/TA: | Karthik Sankaranarayanan, Office: DL486, Email: sankaran@cse |
| Office Hours: | By appointment |
| Course Description: |
This course introduces the fundamental algorithms, concepts, and applications of
computer vision with respect to human-computer interaction. Frequent assignments will explore
computational solutions for integrating vision as input to computers/machines/robots.
Computer vision topics include image formation, image features, image segmentation, shape analysis, object tracking, motion, motion-capture, etc. A term project will be assigned to give students an opportunity to expand on the ideas presented in class and explore interesting computer vision scenarios. |
| Course Objectives: |
Upon satisfactory completion of the course, the student will have learned:
|
| Suggested Prerequisites: | CSE 630 or ECE 352; MATH 568 or 571 (Linear Algebra), or permission from instructor |
| Suggested Texts: | 1) Forsyth and Ponce, Computer Vision: A Modern Approach, First Edition, Prentice Hall, 2003 (ISBN: 0-13-085198-1 ) 2) Shapiro and Stockman, Computer Vision, Prentice Hall, 2001 |
| Grading Plan: | Assignments: 40% Project: 30% Exam: 20% Participation: 10% |
| Policy: | Labs and homework are due in class. No late homework or lab is accepted without substantial documentation of the reason. Excuse from the exam can be accepted only in case of personal sickness requiring medical care or severe accidents in the immediate family. |
Schedule:
| Week | Day | Date | Topic | Reading for Class | HW Assigned |
|---|---|---|---|---|---|
| 1 | Thurs | 9/24 | Introduction | - | - |
| 2 | Tues | 9/29 | Image Formation | FP: Ch. 1; SS: Ch. 2 | - |
| - | Thurs | 10/1 | Noise Removal | FP: Ch. 7.1-7.3, 8.2.4; SS: Ch. 3.1-3.2, 5.3-5.5 | HW-1, [buckeyes_gray.bmp, buckeyes_rgb.bmp, face.bmp] |
| 3 | Tues | 10/6 | Edge Detection | FP: Ch. 8; SS: Ch. 5.6-5.8, 10.3.2-10.3.3 | - |
| - | Thurs | 10/8 | Region Segmentation | FP: Ch. 14.3; SS: Ch. 3.5 | HW-2, HW-2.zip |
| 4 | Tues | 10/13 | 2-D Shape | FP: Ch. 24.2.2, 15.1; SS: Ch. 10.2.3, 3.6, 10.3.4 | - |
| - | Thurs | 10/15 | Image Pyramids | FP: Ch. 7.7, 9.2; Paper | HW-3, HW-3.zip |
| 5 | Tues | 10/20 | Motion | SS: Ch. 9.1-9.3 | - |
| - | Thurs | 10/22 | Motion (con't) | Paper | HW-4, HW-4.zip |
| 6 | Tues | 10/27 | Interactive applications | Paper-1, Paper-2 | - |
| - | Thurs | 10/29 | PCA and Face Recognition | FP: Ch. 22.3; SS: Ch. 14.4; Paper | HW-5, eigdata.txt |
| 7 | Tues | 11/3 | Trajectories | SS: Ch. 9.4 | - |
| - | Thurs | 11/5 | Kalman Filtering | FP: Ch. 17.3, Paper | HW-6, [xtraj.txt, ytraj.txt, kfdata.txt] |
| 8 | Tues | 11/10 | KLT Tracking, Covariance Tracking | KLT Paper 1, KLT Paper 2, Covariance Paper | - |
| - | Thurs | 11/12 | Mean-Shift Tracking | Mean-Shift Tracking Paper | HW-7, target.jpg |
| 9 | Tues | 11/17 | Introduction to Motion Capture | Paper | - |
| - | Thurs | 11/19 | Visit to ACCAD Motion Capture Facility | - | - |
| 10 | Tues | 11/24 | EXAM | - | - |
| - | Thurs | 11/26 | NO CLASS (Thanksgiving) | - | - |
| 11 | Tues | 12/1 | Project Presentations | - | - |
| - | Thurs | 12/3 | Project Presentations | - | - |
