3D Computer Vision Summer Term 2012
Administrative Info
Lecture by Prof. Nassir Navab
Exercises by S. Hinterstoisser and S.Ilic and V. Belagiannis and R. Stauder and V. Haltakov and D.Tan
Type: Lecture Module IN2057
Programs: Informatics (Bachelor, Master)
Informatics (Diploma, Wahlpflichtfach, Theoretische Informatik)
Information Systems (Bachelor), Computational Science and Engineering (Master)
Master Sports Engineering
SWS: 2+2
ECTS: 5 Credits
Course Language: English
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Time, Location & Requirements
Lecture: Tuesday 10:00-11:30 MI 03.13.010
Exercises: Thursday 13:00-14:30 MI 03.13.010
Requirements:
- The classes and exam are in English
- Exams are to be written in English only
- For the intermediate exam, only one handwritten Din A4 (front+back) page with notes is allowed; calculators are allowed (however, computers are not allowed!)
- For the final exam, only one handwritten Din A4 page (front+back) with notes is allowed; calculators are allowed (however, computers are not allowed!)
- The final exam contains 100 points, you need to have 50 points to pass it
- Up to 40 bonus points can be earned from the homework and the intermediate exam
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Site Content
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Announcements
The exam dates are out: please have a look at the bottom of this site. Please note: there won't be any repeat exams for CV1 this semester. If you fail/do not attend the exams the next chance to repeat it is in 2 semesters.
Registration
You need to register for the class and the exam on Tum-Online. Only registered students can take part in the exam!
Homeworks
We will announce special dates on which students have to show their homework either on their own computer or on the computers of the CAMP-Lab. In these sessions, we will check the latest 3-5 homeworks.
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Overview
Making a computer see was something that leading experts in the field of Artificial Intelligence thought to be at the level of difficulty of a summer student's project back in the sixties. Forty years later the task is still unsolved and seems formidable. A whole field, called Computer Vision, has emerged as a discipline in itself with strong connections to mathematics and computer science and looser connections to physics, the psychology of perception and the neuro sciences.
Over the past decade there has been a rapid development in the understanding and modeling of the geometry of multiple views in computer vision. The theory and practice have now reached a level of maturity where excellent results can be achieved for problems that were unsolved a decade ago, and often thought unsolvable. These tasks and algorithms include problems like:
Given two/three/multiple images, and no further information, compute/estimate:
- matches between the images
- the 3D position of the points that generate these matches
- the cameras that generate the images
(Adapted form Hartley & Zisserman's "Multiple View Geometry in Computer Vision")
The fundamental mathematics and a profound comprehension of the basics of projective geometry as well as one-view geometry are the core of the lecture
3D Computer Vision.
Lecture Content
- Intro, motivation & Overview
- 2D Transformations
- Projective 2D Geometry
- 3D Transformations
- Projective 3D Geometry
- Parameter Estimation
- Camera Models
- Camera Calibration
- Conclusion & Discussion
Lecture Schedule
Exercise Schedule
Exams
- Midterm Exam: 19.6.2012, 17:15-18:45, MW 2050.
- Final Exam: 24.7.2012, 10:00-11:30, 102 - Interims Hoersaal 2 .
Readings
- Primary Reading
- Multiple View Geometry in Computer Vision by Richard Hartley & Andrew Zisserman
- General Introduction to 3D Computer Vision
- Three-Dimensional Computer Vision by Olivier Faugeras
- Computer Vision: A Modern Approach by David A. Forsyth & Jean Ponce
- Introductory Techniques for 3-D Computer Vision by Emanuele Trucco & Alessandro Verri
- More Specific Readings
- The Geometry of Multiple Images: The Laws That Govern the Formation of Multiple Images of a Scene and Some of Their Applications by Olivier Faugeras, Quang-Tuan Luong, Theodore H. Papadopoullos; MIT Press; 2001