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UZH-BMINF010 / ETH-151-0632-00L
The course is open to all the students of the University of Zurich and ETH. Students should register through their own institutions.
For a robot to be autonomous, it has to perceive and understand the world around it. This course introduces you to the fundamental computer vision algorithms used in mobile robotics, in particular: feature extraction, multiple view geometry, dense reconstruction, object tracking, image retrieval, event-based vision, and visual-inertial odometry (the algorithm behind Google Tango). Basics knowledge of algebra, geomertry, and matrix calculus are required.
Please check out the course agenda for the exact schedule (coming soon).
Download the Official course program (PDF, 221 KB) - Please note that this is a tentative schedule and the effective content of the lecture can change from week to week.
| Lecture Date | Lecture and Exercise Title | Slides and add-on material |
| 22.09.2016 | Lecture 01 - Introduction to Computer Vision and Visual Odometry | Slides (last update 22.09.2016) Visual odometry tutorial Part I (PDF, 526 KB) Visual odometry tutorial Part II (PDF, 1 MB) |
| 29.09.2016 | Lecture 02 - Image Formation 1: perspective projection and camera models | Slides (last update 06.10.2016) |
| 06.10.2016 | Lecture 03 - Image Formation 2: camera calibration algorithms Exercise 01 - Augmented reality wireframe cube |
Slides (last update 18.10.2016) Additional reading on P3P and PnP problems Exercise 01 (last update 06.10.2016) Introduction to Matlab |
| 13.10.2016 | Lecture 04 - Filtering & Edge detection Exercise 02 - PnP problem |
Slides (last update 13.10.2016) Exercise 02 (last update 13.10.2016) |
| 20.10.2016 | Lecture 05 - Point Feature Detectors, Part 1 Exercise 03 - Harris detector + descriptor + matching |
Slides (last update 20.10.2016) Exercise 03 (last update 25.10.2016) |
| 27.10.2016 | Lecture 06 - Point Feature Detectors, Part 2 | Slides (last update 27.10.2016) Additional reading on feature detection |
| 03.11.2016 | Lecture 07 - Multiple-view geometry 1 Exercise 04 - Stereo vision: rectification, epipolar matching, disparity, triangulation |
Slides (last update 10.11.2016) Additional reading on stereo image rectification Exercise 04 (last update 02.11.2016) |
| 10.11.2016 | Lecture 08 - Multiple-view geometry 2 Exercise 05 - Two-view Geometry |
Slides (last update 16.11.2016) Additional reading on 2-view geometry Exercise 05 (last update 10.11.2016) |
| 17.11.2016 | Lecture 09 - Multiple-view geometry 3 Exercise 06 - P3P algorithm and RANSAC |
Slides (last update 16.11.2016) Additional reading on open-source VO algorithms Exercise 06 (last update 16.11.2016) |
| 24.11.2016 | Lecture 10 - Dense 3D Reconstruction Exercise 07 - Intermediate VO Integration |
Slides (last update 30.11.2016) Additional reading on dense 3D reconstruction Find the VO project downloads below |
| 01.12.2016 | Lecture 11 - Optical Flow and Tracking (Lucas-Kanade) Exercise 08 - Lucas-Kanade tracker |
Slides (last update 30.11.2016) Additional reading on Lucas-Kanade Exercise 08 (last update 01.12.2016) |
| 08.12.2016 | Lecture 12 - Place recognition Exercise 09 - Recognition with Bag of Words |
Slides (last update 07.12.2016) Additional reading on Bag-of-Words-based place recognition |
| 15.12.2016 | Lecture 13 - Visual inertial fusion Exercise 10 - Bundle Adjustment |
Exercise 10 (ZIP, 1 MB) (last update 15.12.2016) |
| 22.12.2016 | Lecture 14 - Event based vision + Scaramuzza's lab visit with live demos Exercise 11 - final VO integration |
70% of the final grade is based on the oral exam (30 minutes, exam date: 19.01.2017) and 30% on a visual odometry (VO) mini-project. Project specification and files can be found in the table below.
| Description | Link(size) |
| Project specification | VO_project_statement_01.pdf (434 kB, last updated 24.11.2016) |
| FAQ | Frequently Asked Questions |
| Solutions to all exercises | all_solns.zip (40.3 kB, last updated 24.11.2016) |
| Parking garage dataset (easy) | parking.zip (208.3 MB) |
| KITTI 00 dataset (hard) | kitti00.zip (2.3 GB) |
| Malaga 07 dataset (hard) | malaga-urban-dataset-extract-07.zip (2.4 GB) |
| Matlab script to load datasets | main.m (2.6 kB) |
All mentioned textbooks are available in the NEBIS catalogue.
The course is currently open to all the students of the University of Zurich and ETH (Bachelor's and Master's). Lectures take place every Monday (from 16.02.2014 to 30.05.2014) from 14:15 to 16:00 in the ETH main building (HG) in room E 1.2. Exercise take place almost every second Tuesday from 10:15 to 12:00 in the ETH main building in room G1.
The course is also offered as a MOOC (Massive Open Online Course) on edX.
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R. Siegwart, I.R. Nourbakhsh, and D. Scaramuzza Introduction to autonomous mobile robots 2nd Edition (hardback) A Bradford Book, The MIT Press, ISBN: 978-0-262-01535-6, February, 2011 |
Since 2007, Prof. Davide Scaramuzza has been teaching this course at ETH Zurich and since 2012 the course has been shared also with University of Zurich. The lectures are based on Prof. Scaramuzza's book Autonomous Mobile Robots, MIT Press. ETH students can watch previous lectures up until 2012 on the ETH multimedia portal.
All lecture slides and videos of past lectures (updated in 2010) can be downloaded from the following links:
