All electronic submissions are due at 11:00 am on the day indicated, unless specified otherwise.
Please note that future homework assignments are tentative based on previous course offerings. We may change assigned homework at any time before it is assigned. Schedule subject to change. Corresponding sections from Sonka, et al. are given at the end where appropriate.
Schedule last updated 2 March.
| Week / Main topic | Monday | Tuesday | Thursday | Friday |
| 1: Intro to images, color | (1) 3/4: Intros (writing, term project), Images and color Start Lab 1: Intro to Matlab (Ch 1) |
(2) 3/5: Color features Due in class: Read sunset paper Lab 1 due Weds 11am. (2,2, 2,4) |
(3) 3/7: Connected components, morphology in Matlab Start Fruit-finder. (13.1-13.3) |
(4) 3/8: Lab 2: Color Laptops for every lab |
| 2: Global and local features, edges | (5) 3/11: Global and local operators, filtering (5.1, 5.3) | (6) 3/12: Edge Masks Lab 2 due (Tues, 11am always) (5.3) |
(7) 3/14: Edge features (5.3) |
(8) 3/15: Lab 3: Edges and filters Due: Fruit-finder 11:00 pm |
| 3: More features | (9) 3/18: Region properties (perimeter, circularity) (8.1-8.3) | (10) 3/19: Spatial moments Lab 3 due (Tues) (8.3) |
(11) 3/21: Classification concepts (9.2.1) | (12) 3/22: Lab 4: Shape. |
| 4: Classifiers | (13) 3/25: Support vector machines (9.2.4) Exam 1 due 5:00 pm. |
(14) 3/26: Finish SVMs and demo. Lab 4 due (Tues) Formally assign sunset detector |
(15) 3/28: Lightning talks for term project, assign teams | (16) 3/29: Lab 5: SVM toolbox. |
| 5: Sunset detector | (17) 4/1: Neural nets (9.3.1) Lab 5 due (Tues) |
(18) 4/2: Neural nets and SVM |
(19) 4/4: Project workday (no class) | (20) 4/5: Lab day: No new lab, but Chris K. will be in class to help with sunset detector |
| Spring Break | ||||
| 6: Deep Learning | (21) 4/15: Convolutional neural networks | (22) 4/16: Convolutional neural networks
Sunset detector part 1 due (Tuesday, 11 pm) |
(23) 4/18: Lab 6: CNNs | (24) 4/19: Exam review (Lab 6 due at end of class) Due: Lit reviews (Sunday, 11:00 pm) |
| 7: Segmentation and object clustering | (25) 4/22: Midterm Exam | (26) 4/23: k-means segmentation (9.2.5)
Sunset detector part 2 due (Tuesday, 11 pm) |
(27) 4/25: Hough transforms (6.2.6) | (28) 4/26: Lab 7: Hough transform Due: Project plans and preliminary work (Sunday, 11:00) |
| 8: Special topics | (29) 4/29: PCA and applications (3.2.10) | (30) 4/30: Bayesian classifiers (9.2.2) Lab 7 due (Tues) |
(31) 5/2: Template matching and HOG (6.4) | (32) 5/3: Lab: Project Milestone Reviews Due: Status report (8:00 am) |
| 9: Special topics and project work | (33) 5/6: Review day | (34) 5/7: Exam 3 | (35) 5/9: Lab: Projects | (36) 5/10: Lab: Project Milestone Reviews Due: Status report (8:00 am) |
| 10: Presentations | (37) 5/13: Presentations: Rainbow detector. (Also do course evaluations) |
(38) 5/14: Presentations: Lane Detection (Jenna, Ryan, Bill, Ding), Palmistry |
(39) 5/16: Presentations: Lane Detection (Charlie, Sam, Addison, Parker), Facial Emotion Recognition |
(40) 5/17: Presentations: Plate Recognition Due: final project (code, report, presentation slides, reflection/partner evals in Moodle (different from presentation evals)), 11:00 PM |