EECS 442: Computer Vision (Winter 2019)
This is the schedule.
Date | Topic | Suggested Reading | Slides | Assignments/Things Out/Things Due |
Thu Jan 10 | Introduction | None | PDF PPTX | |
Tue Jan 15 | Cameras I | S2.1 (for reference H&Z 2, 6) | PDF PPTX | |
Thu Jan 17 | Cameras II | Same as above | (same as above) | HW 1 Out |
Tue Jan 22 | Light And Shading | S 2.2, S2.3 | PDF PPTX | |
Thu Jan 24 | Linear and Non-linear Filtering | S3.2 | PDF PPTX | |
Tue Jan 29 | Detectors and Descriptors I | S4.1 | PDF PPTX | |
Thu Jan 31 | Polar vortex! | | | HW1 Due on Friday Feb 1, HW2 Out |
Tue Feb 5 | Detectors and Descriptors II | S4.1 | PDF PPTX | |
Thu Feb 7 | Transformations I | S2.1, S6 | PDF PPTX | |
Tue Feb 12 | Transformations II | S2.1, S6 | PDF PPTX | |
Thu Feb 14 | Linear Classifiers I | S14 (skim) for context OR ESL 3.1, 3.2 (skim) and ESL 12.3.2 | PDF PPTX | HW2 Due, HW 3 Out |
Tue Feb 19 | Linear Classifiers II | As above | PDF PPTX | Earliest Project Proposal Can Be Submitted |
Thu Feb 21 | Backpropagation | CS231n Backprop Examples | PDF PPTX | |
Tue Feb 26 | Convolutional Neural Nets Part I | CS231n Convnets | PDF PPTX | |
Thu Feb 28 | Midterm | | | |
Tue Mar 5 | Spring Break | | | |
Thu Mar 7 | Spring Break | | | |
Tue Mar 12 | Convolutional Neural Nets Part II | CS231n Convnets | PDF PPTX | |
Thu Mar 14 | Pixel Labeling | Deconvolution artifacts | PDF PPTX | HW3 Due, HW4 Out |
Tue Mar 19 | Detection | | PDF PPTX | Latest Project Proposal Can Be Submitted |
Thu Mar 21 | Optical Flow | S8.4 | PDF PPTX | |
Tue Mar 26 | Tracking and Video Problems | S4.1.4 simple tracking with code | PDF PPTX | |
Thu Mar 28 | Calibration | S6.3 calibration with opencv | PDF PPTX | |
Tue Apr 2 | Single view geometry | | PDF PPTX | |
Thu Apr 4 | Epipolar geometry | S11.1 | PDF PPTX | HW4 Due, HW5 Out
|
Tue Apr 9 | Stereo | S11 | PDF PPTX | |
Thu Apr 11 | Structure from Motion | S7 | PDF PPTX | |
Tue Apr 16 | Advanced Applications: Learning + Geometry | | PDF | Progress Report Due |
Thu Apr 18 | Advanced Applications: Embodiment | | | HW5 Due |
Tue Apr 23 | Advanced Applications: Language | | PDF | Final Projects Due during April 28
|
Re-use policy:
I am extremely grateful to the many researchers who have made their slides and
course materials available. Please feel to re-use any of my materials while
crediting appropriately and making sure original attributions to these generous
researchers is preserved.
S is Computer Vision: Algorithms and Applications by Richard Szeliski, which can be found
here.
H&Z is Multiple View Geometry in Computer Vision by Richard Hartley and Andrew Zisserman, which
can be obtained via the library in electronic form (scroll past the physical copies).
ESL is Elements of Statistical Learning by Hastie, Tibshirani, and Friedman, which can be
found here
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