This course presents the fundamental mathematical tools and concepts used in computer graphics and vision. Each theoretical topic is introduced in the context of practical vision or graphic problems, showcasing its importance in real-world applications.
The theory of each mathematical concept or tool will be introduced and we will then showcase their practical utility in a variety of different applications in computer graphics and vision. The course will cover topics in sampling, reconstruction, optimization, differentiation, quadrature and spectral methods. Applications will include 3D surface reconstruction, structure from motion, camera pose estimation, image editing, character animation, ray tracing, architectural design and shape recognition.
The main goal is to equip the students with the key mathematical tools necessary to understand state-of-the-art algorithms in vision and graphics. In addition to the theoretical part, the students will learn how to use these mathematical tools to solve a wide range of practical problems in visual computing. After successfully completing this course, the students will be able to apply these mathematical concepts and tools to practical industrial and academic projects in visual computing.
The evaluation consists of an oral examination and a set of programming homeworks. The homeworks account for 70% of the final grade, and the oral exam accounts for 30%.
Introduction to Computer Graphics and Computer Vision. Some experience with Matlab and/or SciPy programming.
|Lecturers||Dr. Martin R. Oswald (moswaldinf.ethz.ch), CNB G 103.2 Dr. Cengiz Oztireli (cengizoinf.ethz.ch), CNB G 102.1|
|Assistants||Ian Cherabier (ian.cherabierinf.ethz.ch), CAB G 85.1 Riccardo Roveri (rroveriinf.ethz.ch), CAB G 84.1|
|Course Location||CLA E 4, Mondays 14-16|
|Exercise Location||CLA E 4, Mondays 16-17|