Module Description

Module: 3D Computer Vision

Courses:

TitleTypeHrs/WeekPeriod
3D Computer VisionLecture2Winter Semester
3D Computer VisionRecitation Section (small)2Winter Semester

Module Responsibility:

Prof. Rolf-Rainer Grigat

Admission Requirements:

None

Recommended Previous Knowledge:

  • Knowlege of the modules Digital Image Analysis and Pattern Recognition and Data Compression are used in the practical task
  • Linear Algebra (including PCA, SVD), nonlinear optimization (Levenberg-Marquardt), basics of stochastics and basics of Matlab are required and cannot be explained in detail during the lecture.

Educational Objectives:

Professional Competence

Theoretical Knowledge

Students can explain and describe the field of projective geometry.

Capabilities

Students are capable of

  • Implementing an exemplary 3D or volumetric analysis task
  • Using highly sophisticated methods and procedures of the subject area
  • Identifying problems and
  • Developing and implementing creative solution suggestions.

With assistance from the teacher students are able to link the contents of the three subject areas (modules)

  • Digital Image Analysis 
  • Pattern Recognition and Data Compression
    and 
  • 3D Computer Vision 

in practical assignments.

Personal Competence

Social Competence

Students can collaborate in a small team on the practical realization and testing of a system to reconstruct a three-dimensional scene or to evaluate volume data sets.

Autonomy

Students are able to solve simple tasks independently with reference to the contents of the lectures and the exercise sets.

Students are able to solve detailed problems independently with the aid of the tutorial’s programming task.

ECTS-Credit Points Module:

6 ECTS

Examination:

Written exam

Workload in Hours:

Independent Study Time: 124, Study Time in Lecture: 56


Course: 3D Computer Vision

Lecturer:

Rolf-Rainer Grigat

Language:

English

Period:

Winter Semester

Content:

  • Projective Geometry and Transformations in 2D und 3D in homogeneous coordinates
  • Projection matrix, calibration
  • Epipolar Geometry, fundamental and essential matrices, weak calibration, 5 point algorithm
  • Homographies 2D and 3D
  • Trifocal Tensor
  • Correspondence search

Literature:

  • Skriptum Grigat/Wenzel
  • Hartley, Zisserman: Multiple View Geometry in Computer Vision. Cambridge 2003.