CMSC 426
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Announcements
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General Information |
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Course Policies |
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Course work, late policies, and grading |
There will be (probably) eight problem sets assigned
during the semester. Six of these will include programming assignments to be
done in Matlab. Matlab is
free to download throughout the university. Students can download and install
matlab through Some of these will also include pencil and paper exercises. Two problem sets will be purely pencil and paper exercises. Students will have one or two weeks for each problem set, depending on its size. In addition there will be a computer vision workshop at
the
Homework is due at the start of class. Problems may be turned in late, with a penalty of 10% for each day they are late, but may not be turned in after the start of the next class after they are due. For example, if a problem set is due on Monday, it may be turned in before Tuesday at 2:00, with a 10% penalty, or before Wednesday at 2:00, with a 20% penalty, but no later than Wednesday at 2:00. There will be three exams. Early in the semester, there will be a short,
in-class midterm that will take about half the class. Later, there will be a
midterm that will be in class for a complete class period. The final will be
during the normal final exam time. Each exam will be cumulative, covering all
material learned to that point in the class, with a greater emphasis on
material learned since the previous exam. Exams and problem sets will all be
based on material discussed in class. These will be weighted for the final grade as: Homework 35%, summary of talk, 2%, first midterm 9% second midterm 18%, final exam 36%. Homework assignments are to be written up neatly and
clearly, and programming assignments must be clear and well-documented.
Programs should be written in Matlab. A full paper
copy of all of the homework must be turned in. In addition, we will ask you
to email a copy of all code to the TA, Hao Zhou, at: assignmentcmsc426@gmail.com. Some homeworks and projects may have a special challenge problem. Points from the challenge problems are extra credit. This means that I do not consider these points until after the final course grade cutoffs have been set. Students participating in class discussion or asking good questions will also receive extra credit. |
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Academic Honesty |
All class work is to be done independently. You are allowed to discuss class material, homework problems, and general solution strategies with your classmates. When it comes to formulating/writing/programming solutions you must work alone. If you make use of other sources in coming up with your answers you must cite these sources clearly (papers or books in the literature, friends or classmates, information downloaded from the web, whatever). It is best to try to solve problems on your own, since problem solving is an important component of the course. But I will not deduct points if you make use of outside help, provided that you cite your sources clearly. Representing other people's work as your own, however, is plagiarism and is in violation of university policies. Instances of academic dishonesty will be dealt with harshly, and usually result in a hearing in front of a student honor council, and a grade of XF. (Note, this and other course policies are taken from those of Prof. David Mount). |
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Any student who needs to be excused for an absence from a single lecture, recitation, or lab due to a medically necessitated absence shall: a) Make a reasonable attempt to inform the instructor of his/her illness prior to the class. b) Upon returning to the class, present their instructor with a self-signed note attesting to the date of their illness. Each note must contain an acknowledgment by the student that the information provided is true and correct. Providing false information to University officials is prohibited under Part 9(h) of the Code of Student Conduct (V-1.00(B) University of Maryland Code of Student Conduct) and may result in disciplinary action. The self-documentation may not be used for the Major Scheduled Grading Events as defined below and it may only be used for only 1 class meeting (or more, if you choose) during the semester. Any student who needs to be excused for a prolonged absence (2 or more consecutive class meetings), or for a Major Scheduled Grading Event, must provide written documentation of the illness from the Health Center or from an outside health care provider. This documentation must verify dates of treatment and indicate the timeframe that the student was unable to meet academic responsibilities. In addition, it must contain the name and phone number of the medical service provider to be used if verification is needed. No diagnostic information will ever be requested. The Major Scheduled Grading Events for this course include: a) Midterm - October 9 during the lecture period b) Final exam, as given in University schedule. |
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Academic
Accommodations |
Any student eligible for and requesting reasonable academic accommodations due to a disability is requested to provide, to the instructor in office hours, a letter of accommodation from the Office of Disability Support Services (DSS) within the first two weeks of the semester. |
Below is a tentative schedule for problem sets and lectures.
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Problem Sets |
Assigned |
Due |
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Problem Set 1 : Intro to Matlab, Histograms Matlab template Images to use for your writeup: desert1 desert2 desert3 forest1 forest2 forest3 |
Jan. 29 |
Feb 5 |
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Problem Set 2: K-means clustering and Color Quantization Problem Set Test Code Result for Case 5 forest2 Images for challenge problem leaf1 leaf2 leaf3 leaf4 leaf5 leaf6 See also this paper: |
Feb 5 |
Feb 19 |
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Problem Set 3: Histogram Equalization, Filtering,
Image Gradients |
Feb 19 |
Feb 26 |
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Practice Midterm (not to be turned in) Practice Midterm |
Feb 26 |
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Problem Set 4: Problem Set You will need the following files: BackgroundImages.zip, foreground_image.bmp, BackgroundSubtractionResults.jpg for Problem 1. You will need swanbw.jpg for Problem 2. Your result should look like: swan result. |
March 5 |
March 12 |
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Problem Set 5: Problem Set Brick Test Image. |
March 12 |
March 26 |
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Problem Set 6: Problem Set Image 1 Image 2 Matlab Code |
March 26 |
April 9 |
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Practice Midterm Practice Midterm Answers |
April 9 |
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Problem Set 7: Problem Set Image pair for part e: T3bw.jpg T4bw.jpg. Second image pair for part e: I1L.jpg I1R.jpg. |
April 16 |
April 30 |
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Problem Set 8: Problem Set |
April 30 |
May 7 |
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Review for Final Practice
Final Answers |
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Class slides will typically be posted here, usually minutes before class begins.
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Class Slides |
SLIDES |
NOTES |
READINGS |
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Class 1:Introduction
(Jan 27) |
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Class 2: Pre-assessment and Intro to Matlab (Jan 29) |
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Class 3: Review pre-assessment, Histograms, (Feb 3) |
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Class 4: K-means clustering and color quantization (Feb 5) |
The
Foundations of Color Measurement and Color Perception by Brian Wandell Szeliski, 3.1.4 |
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Class 5: Filtering and
Correlation (Feb 10) |
Tutorial
from Sussex on Convolution Szeliski,
3.4-3.4.1 |
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Class 6: (Feb 12) |
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Szeliski,
4.2.1 up to scale selection |
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Class 7: Fourier Analysis Edge Detection - 1D, Image Gradients (Feb 17) |
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Tutorial
from Sussex on Gaussian filtering and edge detection |
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Class 8: Edge Detection, 2D (Feb 19) |
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Class 9: Human Perceptual Grouping (Feb 24) |
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"Laws of organization in perceptual forms" at http://psy.ed.asu.edu/~classics/Wertheimer/Forms/forms.htm |
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Class 10: Background Subtraction (Feb 26) |
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Class 11: Snow day (March 3) |
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Class 12: Short midterm and review of solutions (March 5) |
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Class 13: Texture (March 10) |
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Texture
Synthesis by Non-parametric Sampling by Efros and Leung. Web
page contains links to the paper and pseudocode. |
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Class 14: Interactive
Segmentation with Graph Cuts, (March 12) |
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Interactive
Graph Cuts for Optimal Boundary & Region Segmentation of Objects in N-D
Images |
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Class 15: SIFT Descriptors and Blob Detection (March 24) |
See paper by Lowe on right |
David G. Lowe, "Distinctive image features
from scale-invariant keypoints," International
Journal of Computer Vision, 60, 2 (2004), pp. 91-110. |
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Class 16: Image Registration and 2D transformations ) (March 26) |
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Dave
Mount's Lecture Notes for Computer Graphics, Chapters 6, 7 and 8 might be
helpful. |
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Class 17: RANSAC, Mosaicing (March 31) |
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Class 18: Perspective Projection and Cameras (April 2) |
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Class 19: 3D Geometry and Stereo (April 7) |
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Class 20: Stereo Matching (April 9) |
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Class 21: Midterm (April 14) |
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Class 22: Recap of midterm, (April 16) |
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Class 23: Motion Flow
Fields , (April 21) |
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Class 24: Optical Flow
(April 23) |
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Class 25: Structure-from-Motion (April 28) |
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Szeliski,
7.2 |
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Class 26: Linear Motion and Lighting (April 30) |
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Class 27: Bag of Words (May 5) |
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Slides from
Svetlana Lazebnik’s class, March 31 |
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Class 28: Detection (May 7) |
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Slides from
Svetlana Lazebnik’s class, March 24 and April 12 |
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Class 29:
Conclusions (May 12) |
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FINAL May 19, 1:30-3:30 |
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