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.
With the help of digital presentations the subjects of the course are presented and explained.
ECTS Breakdown: 3 ECTS = 75h
22.5h Lecture51h Exam Preparation1.5h Exam-----75h
1.5- hour written exam which is typically offered 3 times per term. Attention because of COVID19 only online exams until March 21 are possible. Please arrange an exam date with the lecturer!
This lecture describes 3D acquisition systems where basic mathematical knowledge is a prerequisite