After successful completion of the course, students are able to collect, develop, evaluate and interpret information relevant to 3D computer vision. Students are able to determine requirements and boundary conditions in different areas of 3D computer vision and can apply their acquired knowledge practically in complex 3D computer vision tasks and can work out and develop solutions and arguments for these. Furthermore, students can name, explain and compare the most important theories, principles, concepts and algorithms of 3D computer vision. Their knowledge and understanding corresponds to the state of the art in the field of computer vision.
Please note that the first lecture is on Monday, March 13 at 14:00!
With the help of digital presentations the subjects of the course are presented and explained.
ECTS Breakdown: 3 ECTS = 75h
30h Lecture43.5h Exam Preparation1.5h Exam-----75h
1.5- hour written exam which is typically offered 3 times per term. Attention: If a written exam is not possible due to COVID19, an oral exam will be offered instead.
Ort: TISS
This lecture describes 3D acquisition systems where basic mathematical knowledge is a prerequisite