16-822: Geometry-Based Methods in Vision (Fall 2021)

Day: Monday and Wednesday
Time: 1:25pm-2:45pm
Room: REH Singleton
Lecturer: Michael Kaess
TA: Akash Sharma

The course focuses on the geometric aspects of computer vision: The geometry of image formation and its use for 3D reconstruction and calibration. The objective of the course is to introduce the formal tools and results that are necessary for developing multi-view reconstruction algorithms. The fundamental tools introduced study affine and projective geometry, which are essential to the development of image formation models. Additional algebraic tools, such as exterior algebras are also introduced at the beginning of the course. These tools are then used to develop formal models of geometric image formation for a single view (camera model), two views (fundamental matrix), and three views (trifocal tensor); 3D reconstruction from multiple images; and auto-calibration. Additional advanced topics are discussed as time permits.