Welcome to the homepage of the lecture

Correspondence Problems in Computer Vision

Summer Term 2008


Correspondence Problems in Computer Vision

Lecturer: Dr. Andrés Bruhn
Office hours: Friday, 14:15 - 15:15.

Summer Term 2008

Lectures (2h) with programming/theoretical exercises (2h)
(6 credit points)

Lectures: Wednesday 14-16 c.t., Building E1.3, Lecture Hall 1

First lecture: Wednesday, April 16, 2008.

Tutorials: 2 hours each week, Thursday 16-18 c.t.
Turorials: Building E1.3, Lecture Hall 3 (theory)
Turorials: Building E2.4 (math building), Cip-Pool U009 (programming)

First tutorial: Thursday, April 24, 2008.

PrerequisitesSynopsisPlanned ContentsAssignmentsReferences


Example - Stereo Reconstruction
Example - Motion Estimation


Requires undergraduate knowledge in mathematics (e.g. ''Mathematik für Informatiker I-III'') . Knowledge in image processing or differential equations is useful. The lectures will be given in English.


Correspondence problems are a central topic in computer vision. Thereby, one is interested in identifying and matching corresponding features in different images/views of the same scene. Typical corresondence problems are the estimation of motion information from consecutive frames of an image sequence (optic flow), the reconstruction of a 3-D scene from a stereo image pair and the registration of medical image data from different image acquisition devices (e.g. CT and MRT). Central part of this lecture is the discussion of the most important correspondence problems as well as the presentation of suitable algorithms for solving them.

This class is particularly useful for those students who wish to to pursue a diploma or master thesis in our group in the field of computer vision.



DateTopic
16/4 Introduction, Overview
23/4 Block Matching, Correlation Techniques, Interest Points, Feature-Based Methods
30/4 Optic Flow I: Local Differential Methods, Parameterisation Models
7/5 Optic Flow II: Global Differential Methods, Horn and Schunck
14/5 Optic Flow III: Advanced Constancy Assumptions, Large Motion
21/5 Optic Flow IV: Advanced Data and Smoothness Terms
28/5 Optic Flow V: High Accuracy Methods, Advanced Numerics
4/6 Stereo Matching I: Projective and Epipolar Geometry
11/6 Stereo Matching II: Estimation of the Fundamental Matrix
18/6 Stereo Matching III: Correlation and Variational Methods, Graph Cuts
2/7 Medical Image Registration: Mutual Information, Elastic and Curvature Based Registration, Landmarks
9/7 Particle Image Velocimetry: Div-Curl-Regularisation, Incompressible Navier Stokes Prior


Programming excercises and theoretical assignments are offered as part of the tutorials. The regular attendence of these excercises is requirement for admission to the exam.


DateAssignment
24/4 P1 - Programming Assignment Sources
8/5 P3 - Programming Assignment Sources
22/5 P5 - Programming Assignment Sources
5/6 P7 - Programming Assignment Sources
19/6 P9 - Programming Assignment Sources
3/7 P10 - Programming Assignment Sources


Depending on the numer of participants written or oral exams will take place. The second chance exams is only available for those students who failed the first exam, or who did not take part in the first exam.


There is no specific book that covers the complete content of this class. Many lectures will be based on articls from journals and conferences. However, the following three books cover most topics:

  1. Optic Flow
    A. Bruhn: Variational Optic Flow Computation: Accurate Modeling and Efficient Numerics.
    Ph.D. Thesis, 2006. Available from http://www.mia.uni-saarland.de/bruhn/PhDThesis.pdf

  2. Stereo Reconstruction
    O. Faugeras and Q.-T. Luong: The Geometry of Multiple Images. MIT Press, 2001.

  3. Medical Image Registration
    J. Modersitzki: Numerical Methods for Image Registration. Oxford Press, 2003.


MIA Group
©2001-2019
The author is not
responsible for
the content of
external pages.

Imprint - Data protection