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Computer Vision is the study of inferring properties of the world using digital images
This course is intended for beginning graduate students. We assume students have a rudimentary understanding of linear algebra, calculus, and are able to program in some type of structured language such as C++ and Java. The primary programming language for this class will be MATLAB, which is a convenient platform for mathematical computing involving matrices. There will be five to six (biweekly) homework assignments and several (three to four) programming assignments. We will have a final (in-class or take-home) exam. Grading will be approximately 50% on the homework assignments, 25% on the midterm exam, and 25% on the programming assignments.
| Meetings: | Tuesday 8th-9th periods and Thursday 9th period |
| Instructor: | Jeffrey Ho [jho@cise.ufl.edu] |
| Office: | CSE 360 |
| Office hours: | Friday 2pm-4pm |
| Teaching Assistant: | S M Shahed Nejhum [smshahed@cise.ufl.edu] |
| Office hours: | Monday 3pm-5pm in CSE 309 |
| Note: when e-mailing the instructor and TA, please include [CAP5416] in the subject. |
Grading will be approximately 50% on the homework assignments, 25% on the exam, and 25% on the programming assignments.
Homeworks are due in class and the programming assignments will be due usually before midnight Late homework is frowned upon. 10% of the possible grade is deducted for each day late. If there is ever a situation which prohibits you from turning in your homework on time, you must alert the instructor or TA promptly.
Honor Code
Above all, you must not misrepresent someone else's work as your own. You can avoid this in two ways:
Naturally, even if you give appropriate credit, you will only receive credit
for your original work, so for this class you should stick with option #1.
| Week | Tuesday | Thursday | Suggested Readings | Notes | Comments |
| One | Introduction | Linear Algebra Review | Horn Ch. 1 | Slides | |
| Two | Image formation | Intrinsic and extrinsic camera parameters | Horn Ch. 1-2 | Slides (from MD) | Notes on projective gometry |
| Three | Camera projection and some projective geometry | Image Processing | Horn Ch. 6 | Slides (from MD) | Reading Assignment: Chapters 3-4 in Horn |
| Four | Basic Image Processing | Basic Image Processing | Horn Ch. 6 | Slides 1 and Slides 2 | Reading Assignment: Chapters 6-7 in Horn |
| Five | Edges and Edge Detectors | Edges and Edge Detectors | Horn Ch. 8 | Slides | Six | More Image Features, Corners, etc. | Detecting lines, circles, etc. | Slides |
| Seven | Image Segmentation and Active Contours | Class Cancelled | Slides | Papers | |
| Eight | Image Segmentation/Clustering | More on Spectral Clustering | Slides | Papers | Nine | Camera Calibration | Stereo | Horn Ch. 13 | Slides Slides |
| Ten | Epipolar Geometry, Essential Matrix, Fundamental Matrix | Multiview Reconstruction | Horn Ch. 13 | Slides | |
| Eleven | Stereo Matchings | Photometric Stereo | Horn Ch. 10-11 | Slides | |
| Twelve | Photometry, Shape from Shading | 3D reconstruction | Horn Ch. 10, 11 | ||
| Thirteen | Motion and Flow I | Motion and Flow II | Horn Ch. 12, 17 | Slides | |
| Fourteen | Optical Flows and Pattern Classification | Pattern Classification | Horn Ch. 14 | Slides | |
| Fifteen | Review | No Class | Slides |
Suggested Reading: