EECS 442: Computer Vision (Fall 2019)

This is the tentative schedule.

Date	Topic	Suggested Reading	Slides	Assignments/Things Out/Things Due
Wed Sep 4	Introduction & Projective Cameras I	S2.1 or (for more) H&Z 2, 6	Intro PDF / Cameras PDF PPTX	Projection and Dolly Zoom (Notebook) Homogeneous coordinates (Notebook)
Mon Sep 9	Projective Cameras II	S2.1 or (for more) H&Z 2, 6
Wed Sep 11	Light and Shading	S2.2, S2.3	PDF PPTX
Mon Sep 16	Numerical Linear Algebra Part I	Zico Kolter Review	PDF PPTX	HW1 Out Things Don't Add Up (Notebook) Distance 3 Ways (Notebook) Using a Byte (Notebook)
Wed Sep 18	Numerical Linear Algebra Part II
Mon Sep 23	Linear and Nonlinear filtering	S3.2	PDF PPTX	Convolving Gracefully (Notebook)
Wed Sep 25	Detectors and Descriptors I	S4.1	PDF PPTX	Harris (Notebook)
Mon Sep 30	Detectors and Descriptors II	S4.1	PDF PPTX	HW1 Due, HW2 Out
Wed Oct 2	Transformations I	S2.1, S6	PDF PPTX	Grace in the Middle (Notebook)
Mon Oct 7	Transformations II	S2.1, S6	PDF PPTX
Wed Oct 9	Linear Models	S14 (skim) for context OR ESL 3.1, 3.2 (skim) and ESL 12.3.2	PDF PPTX
Mon Oct 14	Fall Study Break			HW3 Out
Wed Oct 16	Continuous Optimization		PDF PPTX	HW2 Due Friday Oct 18
Mon Oct 21	Backpropagation and Neural Nets	CS231n Backprop Examples	PDF PPTX
Wed Oct 23	Convnets Part I	CS231n Convnets	PDF PPTX
Mon Oct 28	Convnets Part II	CS231n Convnets	PDF PPTX	HW3 Due, HW4 Out
Wed Oct 30	Labeling Pixels	Deconvolution artifacts	PDF PPTX
Mon Nov 4	Detection		PDF PPTX	Project Proposals Due
Wed Nov 6	Optical Flow	S8.4	PDF PPTX
Mon Nov 11	Tracking and Video Problems	S4.14 simple tracking with code	PDF PPTX	HW4 Due, HW5 Out
Wed Nov 13	Calibration and Intro to 3D	S6.3 calibration with opencv	PDF PPTX
Mon Nov 18	Single-View Geometry		PDF PPTX
Wed Nov 20	Epipolar Geometry	S11.1	PDF PPTX
Mon Nov 25	Stereo	S11	PDF PPTX	HW5 Due, HW6 Out, Project Progress Report due anytime Nov 27
Wed Nov 27	Thanksgiving (by 30 minutes!)
Mon Dec 2	Structure from Motion	S7	PDF PPTX
Wed Dec 4	Advanced applications: Learning and Geometry
Mon Dec 9	Advanced applications: embodiment
Wed Dec 11	Advanced applications: language			HW6 Due

Congratulations and thanks to the following who found bugs/typos: Edric Guo, Kyle Marieb, Katie Lee, Tianhong Wen, Adolfo Apolloni

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.

If you find these materials helpful, please drop me a note – I love to hear from people!

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