ETH Zurich - D-INFK - IVC - CVG - Lectures - 3D Vision

3D Vision

This course was called 3D Photography at the time of teaching.

Instructors: Prof. Marc Pollefeys, Dr. Kalin Kolev
Teaching assistant: Bernhard Zeisl, Office hours: Mo. 11:30 - 12:30, Thu. 14:00 - 15:00
Lectures: Mondays from 09:00-12:00 in CAB G51
Prerequisite: Computer Vision lecture from last semester, particularly the camera model, geometric aspects and structure-from-motion. If you have not attended that class, there will be a very short repetition, but you would have to study necessary basics yourself.

Course Descriptions

This course aims to provide students with knowledge on several topics in 3D photography. In each class, student will first be given an introductory lecture on a selected topic from 3D photography. This is followed by students presenting selected papers relevant to the topic of the week. A maximum of 2 papers shall be presented in each lecture. Other students are encouraged to engage in the paper presentations through active discussions. To organize the discussion in a more lively way, each student will be assigned to lead the discussion of an other student's presentation; i.e. this student acts as an "opponent" or moderator and actively supports the discussion by asking relevant questions wrt. the the presented paper and motivates other students to contribute.
Students are also expected to work on a project related to any of the topics in 3D photography through the semester. The project could be done individually or in a team of 2 people. Students must give a final presentation/demo of their projects at the end of the semester.

Grading Scheme

  1. 25%: Paper presentation (incl. discussion moderation)
  2. 75%: Final project which includes a report and presentation/demo

Course Schedule

Please refer to the subpage for the course content and lecture slides.

Course Project and Paper

1. Project

Project Proposal

Each student (group) is required to hand in and present a project proposal within the first three weeks of the semester. Each team will present their project proposal in a 5min presentation to the whole class.
The proposal should be 1-2 pages describing what you want to do in the project, and how you plan to achieve your envisioned results. A good ideas ist to dentify the algorithmic and technological challenges within the project. Try to address each of them individually and explain your considered solutions; also make an attemp to think about alternatives if you believe a particual approach is unstable or likely to fail.

Project assignment deadline: Fr. March 1th. 2013
Proposal submission deadline: Fr. March 8th. 2013 (submit as PDF via email to Kalin and Bernhard)
Proposal presentation: Mo. March 11th. 2013

List of project suggestions, but you are free to propose your own project.

Project Assignment

Please see the list of chosen projects for more details.

2. Paper

Each project group needs to present a paper related to the lecture content.
Please see the list of papers to present by students for more details.

Discussion Forum

There exists a discussion forum page in ILIAS for this course.
Students should sign in using their ETHZ accounts and participate in the discussion forums. Please put all your discussions related to the lectures, paper presentations and projects there.

Available hardware for projects

Students are encouraged to use their own SLR/digital cameras, phones, OpenSource dataset (example from flickr) etc for their projects. However, students who do not own any of the equipment could also make arrangements with our lab for any of the listed equipment. Students with project idea that require any other special equipment should talk to us.

Following hardware is available:
  • Kinect Sensor (several available)
  • Andriod phone (Google nexus phone, Samsung Galaxy S3) (Can be organized if students do not have their own phones)
  • GoPro HD Hero (several available)
  • Fuji Finepix Stereo Camera (Can be organized if needed)
  • Pointgrey cameras

Some useful links

Open Source Computer Vision (OpenCV) - lots of computer vision algorithms
Point Cloud Library (PCL) - provides interface to Kinect sensor and 3D modeling algorithms
Camera calibration toolbox for Matlab

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