| Component | Percentage | Date |
|---|---|---|
| Midterm: | 20% | TBD |
| Final: | 25% | 05/12 |
| Project: | 25% | 05/15 |
| Homework: | 15% | |
| Presentation: | 10% | |
| Participation: | 5% |
| Date | Note |
|---|---|
| 03/26/21 | The second half of the course will consist of paper reading and presentations. Please see the reading list [link] and pick a paper you would like to present. The reading and paper presentation assignment has been updated. There were typos with the selection deadline (04/02) and clarification that your mini paper reports will be submitted through Webcampus.
Project description [pdf] and examples [pdf] are posted for selection by 04/02. Please note, you may use paper not on the list. |
| 01/29/21 | Homework 1 is delayed. Use the weekend to finish off a nice submission. You can find a latex template here [link]. Be sure to download the associated images in pdf form here [im1][im2][im3]. |
| 01/11/21 | Welcome to Fall 2021. This class utilize Matlab/Python/OpenCV/TensorFlow for programming and Latex for assignments. |
| Week | Date | Lecture Topic | Reading | Assignment |
|---|---|---|---|---|
| 1 | 01/18 M | Course Info [pdf][vid] Intro [pdf][vid] | GW Ch 1 [pdf], 2 [pdf] | HW00 [pdf] Due -- |
| 01/20 W | Image Fundamentals [pdf][vid1][vid2] | |||
| 2 | 01/25 M | Spatial Filtering [pdf][vid] | GW Ch 3 [pdf] | HW01 [pdf] Due |
| 01/27 W | Spatial Filtering [vid] | |||
| 3 | 02/01 M | Color IP [pdf][vid] Morphology [pdf][vid@46:23] | GW Ch 6 [pdf], 9 [pdf] | HW02 [pdf] Due Su 2/07 |
| 02/03 Th | Frequency Domain Filtering [pdf][vid] | |||
| 4 | 02/08 M | Frequency Domain Filtering [pdf][vid] | GW Ch 4 [pdf] | HW03 [pdf] Due Su 2/21 |
| 02/10 W | Segmentation [pdf] [vid] | |||
| 5 | 02/15 M | President's Day Holiday | GW Ch 10 [pdf] | |
| 02/17 M | Segmentation [vid] | |||
| 6 | 02/22 M | Motion [pdf] [vid] | Szeliski Ch 8 Sonka Ch 16 [pdf] |
HW04 [pdf] Due Su 3/07 |
| 02/24 W | Motion [vid] | |||
| 7 | 03/01 M | Keypoints [pdf][vid] | Szeliski Ch 4 [pdf] [Stauffer and Grimson 1999] [pdf] |
|
| 03/03 W | Mixture of Gaussian Background Model [pdf] [vid] | |||
| 8 | 03/08 M | Project Introduction [pdf] Reading List [link] |
Project Description [pdf] Project Examples [pdf] Reading List [link] |
HW05 [pdf] Due Su 3/28 |
| 03/10 W | Midterm [vid] | |||
| 9 | 03/15 M | Spring Break | ||
| 03/17 W | Spring Break | |||
| 10 | 03/22 M | Object Recognition [pdf][vid] | Sonka Ch 9 [pdf] Szeliski 2e Ch 6 [Viola Jones 2001] [pdf] |
Paper Presentation [pdf] Due F 04/02 |
| 03/24 W | Viola-Jones Detector [pdf][vid] | |||
| 11 | 03/29 M | Machine Learning (ML) Overview [pdf][vid][vid2] | Geron Ch 1 [pdf] Geron Ch 10 [pdf] |
|
| 03/31 W | Artificial Neural Network (ANN) Overview [pdf][vid] | |||
| 12 | 04/05 M | Deep Computer Vision Using CNNs [pdf][vid] | Geron Ch 14 [pdf] [Maldonado 2007] [pdf] |
|
| 04/07 W | Traffic Sign Recognition with SVM [pdf][slides][WebEx] CNNs [vid] |
|||
| 13 | 04/12 M | Normalized Cuts Segmentation [pdf][slides][WebEx] CNNs [vid] |
[Shi and Malik 2001] [pdf] [Razavian 2014] [pdf] |
|
| 04/14 W | CNNs [WebEx] | |||
| 14 | 04/19 M | Off-the-Shelf CNN Features [pdf][slides][WebEx]
Fast RCNN [pdf][slides][WebEx] |
[Girshick 2015] [pdf] [Chiang 2019] |
HW06 [pdf] Due Su 5/02 |
| 04/21 W | Food Calorie Prediction with Mask RCNN [pdf][slides][WebEx] | |||
| 15 | 04/26 M | 3D PointNet [pdf][slides][WebEx] Object Detection [WebEx] |
[Qi 2017] [pdf] [Caltagiorne 2018] [pdf] |
|
| 04/28 W | Deep Lidar-Camera Fusion [pdf][slides][WebEx] Two-Stream Detection [WebEx] |
|||
| 16 | 05/03 M | Project Presentations [WebEx] One-Stream Detection [WebEx] |
Deep Detection [pdf] and Segmentation [pdf] |
|
| 05/05 W | Project Presentations [WebEx] | |||
| 17 | 05/10 M | Review [WebEx] |
- | |
| 05/12 W | Final [WebEx] |