TeachingSs09CV

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

3D Computer Vision Summer Term 2009

Administrative Info

Lecture by Prof. Nassir Navab
Exercises by Diana Mateus , Stefan Hinterstoisser and Loren Schwarz

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

Time, Location & Requirements

Tuesday 10:30 - 12:00 MI 03.13.010

Exercises: Thursday 13:00 - 14:30 MI 03.13.010

Requirements:

  • The classes and exam are in English
  • For the intermediate exam, only one handwritten Din A4 (front+back) page with notes is 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

Site Content

Announcements

ALERT! NEW The final exam results and the lecture grades have been e-mailed to everyone who has participated at least in the Midterm exam. If you did not receive an e-mail with your grades today, please contact us. If you want to see your final exam, stop by our office next week (17.08.-20.08.).

ALERT! NEW Those of you who were not able to participate in the final exam on July 28, please provide a doctor's note confirming your sickness. Drop us an e-mail and we will announce a date for the repetition exam.

Registration

Neither the class nor the exercises require any registration.

Homeworks

Students have exactly one week to solve the homework (Solutions must be sent before the next exercise session)

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

  1. Intro, motivation & Overview
  2. 2D Transformations
  3. Projective 2D Geometry
  4. 3D Transformations
  5. Projective 3D Geometry
  6. Parameter Estimation
  7. Camera Models
  8. Camera Calibration
  9. Conclusion & Discussion

Lecture Schedule

Date Conducted by Topic Material/Literature
Tue, April 21  Prof. Nassir Navab Introduction and Motivation Introduction (without Videos)
Thu, April 23 Prof. Nassir Navab Basic Transformations & 2D Projective Geometry Lecture 1
Tue, April 28 Prof. Nassir Navab Transformations & 2D Projective Geometry Lecture 2
Thu, April 30 Prof. Nassir Navab 2D Projective Geometry Lecture 3
Tue, May 12 Prof. Nassir Navab Parameter Estimation: Linear Estimation, DLT, Cost Functions Lecture 4
Thu, May 14 Prof. Nassir Navab Parameter Estimation: Sampson Error, Statistical Cost Functions  
Tue, May 26 Prof. Nassir Navab Parameter Estimation  
Tue, June 2 no class due to holiday (Pfingsten)    
Tue, June 9 Dr. Slobodan Ilic Non-linear Parameter Estimation Lecture 7
Tue, June 16 Prof. Nassir Navab Algorithm Evaluation & Error Analysis Lecture 8
Thu, June 25 Prof. Nassir Navab Camera Models Lecture 9
Tue, June 30 Prof. Nassir Navab Computation of the Projection Matrix  
Tue, July 14 Prof. Nassir Navab Camera Calibration Lecture 11
Thu, July 16 Prof. Nassir Navab Modeling and Correction of Distortion  

Exercise Schedule

Date Conducted by Topic Exercises Solutions Homework due
Tue, May 5 Diana Mateus, Stefan Hinterstoisser, Loren Schwarz Homogeneous Coordinates, Hierarchy of Transformations (2D)   Thu, May 14
Thu, May 7 Diana Mateus, Stefan Hinterstoisser, Loren Schwarz Hierarchy of Transformations (3D), Rotation Representation   Thu, May 21
Tue, May 19 no exercise due to Studentische Vollversammlung        
Thu, May 21 no exercise due to holiday (Christi Himmelfahrt)        
Thu, May 28 Diana Mateus, Stefan Hinterstoisser, Loren Schwarz Cross-Ratio of Points and Lines   Thu, June 4
Thu, June 4 Diana Mateus, Stefan Hinterstoisser, Loren Schwarz Singular Value Decomposition, Pseudoinverse   Thu, June 11
Thu, June 11 no exercise due to holiday (Fronleichnam)        
Tue, June 23 Diana Mateus, Stefan Hinterstoisser, Loren Schwarz Correction of Midterm Exam      
Thu, July 2 Diana Mateus, Stefan Hinterstoisser, Loren Schwarz Error Models, Normalized DLT, Mosaicing   Thu, July 9
Tue, July 7 Diana Mateus, Stefan Hinterstoisser, Loren Schwarz Error Models, Non-linear Parameter Estimation   Tue, July 14
Thu, July 9 Diana Mateus, Stefan Hinterstoisser, Loren Schwarz Error Propagation   Tue, July 21
Tue, July 21 Diana Mateus, Stefan Hinterstoisser, Loren Schwarz Projection Matrix, Matrix Decomposition, Zhang Calibration 1   Thu, July 28
Thu, July 23 Diana Mateus, Stefan Hinterstoisser, Loren Schwarz Zhang Calibration 2    

Exams

  • Midterm Exam: Thursday, June 18
  • Final Exam: Tuesday, July 28 in MW2050, at 10.30-12.00

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

TeachingForm
Title: 3D Computer Vision
Professor: Nassir Navab
Tutors: Diana Mateus, Stefan Hinterstoisser, Loren Schwarz
Type: Lecture
Information: 2+2 SWS, 5 ECTS, Theoretische Informatik, Wahlpflichtfach
Term: 2009SoSe
Abstract: The class covers projective and one-view geometry for Computer Vision Applications.


Edit | Attach | Refresh | Diffs | More | Revision r1.57 - 10 Feb 2011 - 13:59 - LorenSchwarz

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