This course covers algorithms and applications to extract 3D information (especially shape) from images. It starts with the camera model and calibration, 2D and 3D projective geometries and extracting feature points. Then it covers passive 3D reconstruction techniques such as single view reconstruction, structure from motion, shape from silhouettes. Active sensing techniques (time of flight cameras, structured light, laser scanners etc.) that directly obtain 3D data are also briefly covered.

Course Objectives

To teach the imaging geometry of cameras. To describe the algorithms used in 3D information and shape extraction and to improve ability to implement these algorithms. To form acquaintance with the applications of this research area. To improve the ability of written and oral presentation.

Recommended or Required Reading

Computer Vision: Algorithms and Applications, Richard Szeliski, Springer, 2010.

Learning Outcomes:

Grading

Midterm 25%

Homework 15%

Presentation 30%

Final 30%