Fall 2016 - Vision Algorithms for Mobile Robotics
The course is open to all the students of the University of Zurich and ETH. Students should register through their own institutions.
Goal of the Course
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.
Time and location
Please check out the course agenda for the exact schedule (coming soon).
Course Program, Slides, and Add-on Material
Official course program (please notice that this is a tentative schedule and that 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 Visual odometry tutorial Part II|
|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 problemsExercise 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 rectificationExercise 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 geometryExercise 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 algorithmsExercise 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 reconstructionFind 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-KanadeExercise 08 (last update 01.12.2016)Exercise 08 Solutions (last update 15.12.2016)|
|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
Exercise 09 (last update 08.12.2016)Exercise 09 Solutions (last update 15.12.2016)
|15.12.2016||Lecture 13 - Visual inertial fusion Exercise 10 - Bundle Adjustment||Slides (last update 15.12.2016)
Advanced Slides for intrerested reader
Additional reading on visual-inertial fusion
Exercise 10 (last update 15.12.2016)Exercise 10 Solutions (last update 25.12.2016)
|22.12.2016||Lecture 14 - Event based vision + Scaramuzza's lab visit with live demos Exercise 11 - final VO integration||Slides (last update 15.12.2016)
Additional reading on event-based vision
Oral Exam Questions (last udpate 01.01.2017)
The oral exam will last 30 minutes and will consist of one application question followed by two theoretical questions. This document contains a "non exhaustive" list of possible application questions and an "exhaustive" list of all the topics that you should learn about the course, which will be subject of discussion in the theoretical part.
Grading and VO project (last udpate 03.01.2017)
70% of the final grade is based on the oral exam (30 minutes, exam date for UZH: Jan. 19 and 20. Exam date fo ETH from Jan. 31 until Feb. 3) and 30% on a visual odometry (VO) mini-project. Project specification and files can be found in the table below. The deadline for the project is Sunday, 08.01.2017, 23:59:59, and it can be submitted via e-mail to the assistants (add links to external resources if the file size limit is exceeded).
|Project specification||VO_project_statement_02.pdf (999.7 kB, last updated 01.12.2016)|
|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)|
Recommended Textbooks(All available in the NEBIS catalogue)
- Robotics, Vision and Control: Fundamental Algorithms, by Peter Corke 2011. The PDF of the book can be freely downloaded (only with ETH VPN) from the author's webpage.
- Computer Vision: Algorithms and Applications, by Richard Szeliski, Springer, 2010. The PDF of the book can be freely downloaded from the author's webpage.
- An Invitation to 3D Vision, by Y. Ma, S. Soatto, J. Kosecka, S.S. Sastry.
- Multiple view Geometry, by R. Hartley and A. Zisserman.
Spring 2015 - Autonomous Mobile Robots
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 given as an MOOC (Massive Open Online Course) under edX.
Introduction to autonomous mobile robots 2nd Edition (hardback)
A Bradford Book, The MIT Press, ISBN: 978-0-262-01535-6, February, 2011
The book can be bought during the first lecture or on Amazon.
Archived slides, videos, and lecture recordings
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. Recordings of previous lectures (until 2012) can be watched or downloaded, only by ETH students, here.
You can download all the lecture slides and videos of past lectures (updated in 2010) from the following links:
- Power Point slides: AMR_lecture_slides.zip
- Videos Part 1: AMR_lecture_videos_1.zip
- Videos Part 2: AMR_lecture_videos_2.zip
- Videos Part 3: AMR_lecture_videos_3.zip
- Videos Part 4: AMR_lecture_videos_4.zip
- Videos Part 5: AMR_lecture_videos_5.zip