| Lectures: | Tuesday, Thursday 12:30 pm - 2:00 pm in MCS B33 |
| Instructor: | Prof. Margrit Betke |
| Grader: | Zheng Wu | Class web page: |
http://www.cs.bu.edu/faculty/betke/cs585 |
| Class mailing list: |
cs585@cs.bu.edu | Contact Information: |
| Staff | Phone | Office Hours | Office | |
| Margrit Betke | betke @ cs.bu.edu | 353-8919 |
Mondays 12:30-1:30, Tuesdays 11-12, 4-5
and by appointment |
MCS 286 |
| Zheng Wu | wuzheng @ cs.bu.edu |
358-3246 (during office hours) 353-TBA (otherwise) |
Wednesdays TBA
and by appointment |
PSY 228A |
Seeing Me in My Office:
Please feel free to stop by my office anytime. My office is in MCS
286 (111 Cummington St). I am generally around every day, but often
in meetings, so the best time to reach me is during office hours. You
can also make an appointment by email. I'm happy to talk with you
about the course, computer vision research, your plans for the future,
or anything else. Check out my
personal web page to get to know me a little.
Grader Responsibilities:
TBA is responsible for
helping you out during his office hours and grading the homework.
Please email him if you have questions about your homework grades.
Our goal is to build computer systems that analyze images automatically and determine what the computer ``sees'' or ``recognizes.'' The course gives you a fundamental introduction to computer vision methods. Applications include human-computer interfaces, face detection, medical image processing, infrared image analysis of animals, and vision systems for intelligent vehicles.
Prerequisites: 1 year programming experience (e.g., C, C++ or Java at CS 112 level), linear algebra, and calculus.
Handouts: The updated course syllabus and most handouts are made available online. Check our course web page at least once a week for homework assignments and other information.
Textbook: Robot Vision by BKP Horn, MIT Press. If you are concerned about the book's price, you could use the book I placed on reserve in the Science Library.
Computing Environment: You will use one of the Computer Science Department's servers csa, csa2, csa3, or csb.bu.edu to download code and submit programming solutions. Make sure to add yourself to the course mailing list by typing csmail -a cs585.
To get an account, go to the Computer Science Department's Undergraduate Lab located at 730 Commonwealth Ave. You can work on various platforms in the lab there (and have immediate access to the computing staff). You can also access the servers remotely using scp and ssh. I discourage the use of telnet and ftp due to security problems.
For your course projects, you can also use the Human-Computer Interface Lab in 64 Cummington St. If you want to use the lab for your project, talk to me first, since access to the lab is restricted.
Homework: The homework includes bi-weekly programming, reading assignments, and problem sets. The due dates are listed below. Programs and reports must be submitted electronically. Solutions to problem sets must be submitted in class. They do not need to be typed but should look professional. Guidelines for submission are provided with each assignment. Late solutions will be levied a late penalty of 20% per day (up to three days). After three days, no credit will be given.
Project: Please read the project guidelines. You can propose your own project topic or use one of my project suggestions. I will discuss your project's scope, design, and presentation with you in my office hours and provide guidance throughout the semester. You may work by yourself or in a group. You will present the final project in class at the end of the term.
Computer Vision Talks: Students are encouraged to attend the CS Department Colloquia (M 11-12 or as noted, MCS 135) and the Image and Video Computing Group talks (Thursdays 4-5 pm, MCS 135 or MCS 205) on course related topics.
Class Participation: Come to class and participate regularly. Reading the textbook and listening in class will only give you a "passive understanding" of the material. I encourage discussions in class to help you acquire an "active understanding" of the material so that you can evaluate existing computer vision techniques critically and develop your own creative solutions. I may give a short (announced) quiz so that shy students have a chance to discuss a topic in written form.
Take-Home Exam: There will be one take-home exam on the material discussed in the class and practiced with homeworks. To prepare for the exam, come to class, participate in our discussions, and keep up with homework assignments. There will not be a final in-class exam.
Grading Policy: Your final grade will be determined roughly as follows:
Collaboration and Academic Integrity
You are encouraged to collaborate on the solution of the homework. If you do, you must code up your solutions on your own and acknowledge your collaborators. Each student must submit his or her own electronic version of the solutions. You can request an exception to this rule for your final project. If you use algorithms or code that are not your own original work and that were not provided in class or discussed in the textbook, you must give a detailed acknowledgment of your source .
You are not allowed to collaborate on the solution of the take-home exam. Sources must be acknowledged.
Cheating and plagiarism are not worthy of Boston University students. I expect you to abide by the rule stated above and the standards of academic honesty and computer ethics policy described in http://www.bu.edu/computing/ethics/ and http://www.bu.edu/cas/academics/programs/conductcode.html
Image and Video Computing is an elective course that will introduce you to an exciting topic in computer science. It should be fun and not too much of a struggle for you. Make sure that you have had the prerequisites. Depending on your level of programming experience and/or mathematics background, the course may be challenging for you. If you do not understand the material, ask for help immediately. Ask questions in class. If one student is confused about something, then maybe others are also confused and grateful that someone asked. Come and see me or Rui for help or send us email. Our task is to help you learn a very interesting topic!
Course Schedule
| Date | Topics | Readings | Assignments |
| 1/17 | Course Introduction: Why study IVC? Image Formation, Image and Video Formats, Color, Face Detection. | Ch. 1, Handout | P1 out |
| 1/22-24 | Motion: Template-based Tracking (Traffic Applications, Camera Mouse), Human Computer Interfaces for People with Disabilities, Similarity Functions, Image Pyramids | Handout, Betke et al. 2002 | 1/24: A1 out |
| 1/29-31 | Binary Image Analysis: Orientation, Circularity, Object Skeletons, Neighborhoods. Virtual Colonoscopy. | Last day to add class, Wednesday, 1/30.Ch. 3, Handout | 1/31: A1 due, A2 out |
| 2/5-7 | Binary Image Analysis: Component
Labeling, Morphology, Thinning, Swelling, Circuit Board
Inspection, Segmentation: Thresholding | Ch. 4, Ch. 5, Handout | A1 graded |
| 2/12-15 | Region Merging, Splitting, Growing, Region Representations, Medical Image Databases, Tumor Detection in Computed Tomography Images | Handout, Wang et al. 2005, Petrakis and Faloutsos, 1997 Ko and Betke, 2001 | 2/15: A2 due, A3 out |
| 2/19 | No Class. Monday schedule. | ||
| 2/21 | Object Recognition, Nonlinear
Optimization, Simulated Annealing
Last day to drop class (without a 'W' grade). |
Betke and Makris, 1995 | A2 graded |
| 2/26-28 | Image Smoothing, Edge Detection, Active Contours | Ch. 8, Williams and Shah, 1992 | 2/28: A3 due |
| 3/4-6 | Multiple Image Analysis, Absolute Orientation, Quaternions, Range Image Registration. Lung Surface Alignment and Nodule Registration. | Ch. 18.10, Ch. 13, Betke, Hong et al. | 3/6: P1 due (in class), A4 out, P2 out |
| 3/8-3/16 | Spring Break | ||
| 3/18-20 | Relative Orientation Friday, 3/21: Last day to drop class (with a 'W' grade). |
Handout | A3 graded |
| 3/25-27 | Optical-flow-based Tracking, Horn-and-Schunk Algorithm, Structure from Motion | Ch. 12, 17, Handouts | 3/27: A4 due, Exam out |
| 4/1-8 | Tracking Methods and Applications: Facial Feature Tracking, Interactive Graphics | Freeman et al., handout of Yacoob's work. Shugrina et al., handout on facial action units. | 4/3: Exam due, A4 graded |
| 4/10-22 | Tracking: Kalman Filters, alpha-beta filters, particle filters. Bat tracking | Handout on bat tracking, Betke et al., 2007 | 4/10: Exam graded |
| 4/24 | Lenses, Photometric Stereo, Shape from Shading | Ch. 10, 11, 17 | 4/22: A5 out |
| 4/29, 5/1 | Student Projects: Guidelines, Topics and Schedule | 4/29: P2 due, 5/1: A5 due |
Assignments
Assignments A1-A5 will have some programming components. Results.
(Potential) Topics (links will became active when assignment is announced):
These assignments relate to your projects. For project ideas, check here.
Exam
The take-home exam is due on Thursday, April 3, in class. It is not available electronically. Make sure to come to class on Thursday, March 27, to receive a copy.
Check out http://www.cs.bu.edu/faculty/betke/links.html if you need additional ideas for your class project, if you are looking for a job in computer vision, or if you are interested in computer vision research. You will find a list of links to computer vision conferences, journals, research groups, and companies.
Calculus Background
You may find the first few chapters of these notes by Cain and Herod useful, in particular, partial derivatives, Taylor polynomial, Multivariate Taylor polynomial.
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