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(Sept 2) Welcome to CMSC426!
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(Sept 9) For today's class notes check out Topic 16: Histogram Equalization
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(Sept 11) New notes uploaded, check out Topic 17: Correlation and Convolution
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(Sept 17) Homework 1 uploaded, due Oct 5 23:59
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(Sept 25) Due to some timing conflicts I (the TA) am tentatively switching the office hours from Friday to Monday (2pm to 4pm), if this is an incovenient timing for you please inform me via mail
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(Oct 1) New notes uploaded, Topic 18 and 19
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(Oct 6) Due to a lot of students not understanding the deadline system, the deadline of Homework 1
is POSTPONED for a week to 12th October. Do remember you can submit till the deadline for the NEXT homework,
but submitting in time gets you extra credit
This will be the only time a deadline extension will be given.
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(Oct 10) Homework 2 uploaded, due Oct 24 23:59
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(Oct 20) IMPORTANT NOTE: The room for meeting with the TA for office hours has changed to AVW4103. This is because all 4xx level courses have this room to meet.
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(Oct 27) Homework 1 has been graded, and the grades are uploaded in the grades server. A few student solutions have been posted as representative of what we were looking for
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(Oct 30) Midterm posted, deadline is Sunday (2nd Nov) midnight
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(Nov 10) The midterm has been graded, the class did extremely well! The scores have been uploaded. The extra credit for question 3 has not been given yet, I will upload those later. Sample solutions and rubric will be uploaded soon.
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(Nov 20) Homework 3 uploaded, due Dec 3 23:59. Do remember this is the final day to submit Hwk 2
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(Dec 1) As mentioned on Piazza I will not be taking todays office hours due to me not being well, mail me if you have any questions
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(Dec 4) Homework 4 posted, due Dec 19 23:59. Do remember this is the final day to submit Hwk 3
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(Dec 13) Homework 2 has been graded, and the grades are uploaded in the grades server. A representative student solution has been posted
Course Outline
In this class we will cover the following topics:
- 1. Introduction:
- What is Computer Vision? Ongoing Research and Application Areas.
- 2. Image Formation:
- Geometric aspects, Radiometric Aspects, Digital Images, The Human Eye,
Camera parameters
- 3. Filters:
- Linar Filters and Convolution, Spatial Frequency and Fourier Transform,
Sampling and Aliasing, Noise Reduction small
- 4. Edge Detection:
- Gradient based edge Detectors, Laplacian, Parametric Models
- 5. Other Image Features:
- Hough Transform, Ellipse fitting, Deformable contours
- 6. Lightness and Color:
- Surface Reflectance, Recovering Lightness, The Physics of Color, Human Color Perception, Color Representations
- 7.Camera Calibration :
- Intrinsic Parameters, Extrinsic Parameters
- 8. Multiple View Geometry:
- Stereo, The Correspondence Problem, Epipolar Geometry, 3D Reconstruction
- 9. Motion:
- The Image Motion Field, Estimation of 3D Motion and Structure,
Segmentation on the basis of different Motion, Image Compression
- 10. Shape from Single Image Cues:
- Surface Descriptions, Shape from Contours, Shape from Shading,
Shape from Texture.
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Reading List
There is no required text. We will distribute material from a variety of sources.
Grading
TBD
Lecture Notes
- Topic 1: Image Formation 1 [pdf] [ppt]
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- Topic 2: Projective Geometry [ppt] (10 MB)
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- Topic 3: Linear Algebra Review [ppt]
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- Topic 4: Camera Calibration [pdf]
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- Topic 4: Filtering [ppt]
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- Topic 5: Edge detection [ppt]
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- Topic 6: Resampling [ppt] (Slides from Univ. of Washington)
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- Topic 7: Image motion [ppt]
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- Topic 8: Statistics on image features: Review of statistical concepts [ppt] [Website on illusions]
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- Topic 9: Stereopsis [ppt]
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- Topic 10: Epipolar Geometry [ppt] (8 MB)
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- Topic 11: Interpretation of image motion fields [ppt]
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- Topic 12: 3D motion estimation from image derivatives [ppt]
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- Topic 13: Shape from Shading [pdf] (from Daniel DeMenthon)
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- Topic 14: Texture [ppt] (5.5 MB)
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- Topic 15: Tracking with Kalman Filters [pdf] (from Daniel DeMenthon)
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- Topic 16: Histogram Equalization [pdf]
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- Topic 17: Correlation and Convolution [pdf]
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- Topic 18: Image Formation 1 [pdf]
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- Topic 19: Perception for Robots 1 [pdf]
Additional Resources
Suggested book for reference: "Multiple view geometry in computer vision" by Hartley and Zisserman
Some slides for using MATLAB in Image Processing
Online resource of computer vision topics (contains short descriptions and tutorials on basic and advanced topics)
Image Processing Learning resources
Web Accessibility
