Prof. Nassir Navab
Exercises by Dr. Selim Benhimane and Hauke Heibel
2+2 SWS, 5 ECTS, Theoretische Informatik, Wahlpflichtfach
Exercises: Thursday 13:00-14:30 MI 03.13.008
Requirements: * The classes and exam are in English
* The final exam is written and only notes are allowed (no book)
* 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
First Exercises: Thursday, 19 April 2007 at 13:00-14:30 MI 03.13.010
Homework must be handed over at latest until the beginning of the following exercise. Programming assignments should be sent to the person who conducted the exercise in which the homework was given. Written assignments should be put in the blue homework box at the chair (in front of room MI 03.13.052). Solutions for the exercises and homework can be found on the web-site one week after the exercise in which the homework was given. Final grades will only be given at the end of the term. If somebody needs personal feedback, you can drop by in the office of the person who conducted the exercise in which the homework was given. Final Exam in MI 03.13.010 (90 minutes) at 10:30
No book, no lecture slides allowed.
Only a two-sided written A4 paper is allowed during the test .
It contains your own notes and should be hand written.
|Title:||3D Computer Vision II|
|Professor:||Prof. Dr. Nassir Navab|
|Tutors:||Dr. Selim Benhimane and Hauke Heibel|
|Information:||2+2 SWS, 5 ECTS, Theoretische Informatik, Vertiefungsfach|
|Abstract:||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 modelling 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" This tasks and algorithms as well as the methods which allow us to reason about the quality of our results are the core of the lecture 3D Computer Vision II. This lecture deals with multiple view geometry problems and having attended 3D Computer Vision I is of great benefit, however, it is not, in any case, compulsory.|