One of the key challenges in
visual computing is to measure geometric properties of objects and scenes and to
recover 3D models of shape and appearance from images. Recent advances
in computer vision, computer graphics and photogrammetry
have resulted in effective techniques to capture models of static and
dynamic scenes. These
have a wide range of applications, such as generating 3D content for
web, computer games and 3D TV, but also digitizing cultural heritage or
enable virtual tourism, 3D tele-presence,
robot navigation and forensics.
The goal of this course is
to provide students with a good understanding of how 3D object shape
and appearance can be estimated from images and
videos. The main concepts and techniques will be
studied in depth and practical algorithms and approaches will be
discussed and explored through exercises and a course
After attending this course
- Understand the concepts that
allow recovering 3D shape from images.
- Have a good overview of the
state of the art in geometric computer vision.
- Be able to critically
analyze and asses current research in the area
- Implement components of a 3D
The course will cover the following topics a.o.
camera model and calibration, single-view metrology, triangulation, epipolar and multi-view
geometry, two-view and multi-view stereo, structured-light, feature
tracking and matching, structure-from-motion, shape-from-silhouettes
and 3D modeling and applications.
The target audience of this course are Master or PhD students, or
advanced Bachelor students, that are interested in learning about geometric computer vision and related topics.
- In the first part of the
class the main geometric concepts of computer vision approaches will be covered in detail.
- Exercises and programming
assignments will be given to support this.
- In the second part of the
class relevant papers will be discussed to explore the
- Students will implement
components of a 3D photography system as a course project.
The course is open to all students that have taken an introductory
course in computer vision or computer graphics, or have equivalent
that are not sure if they satisfy the prerequisites should contact the
The material for this course will consist of slides, course notes and
papers. The slides will be available on-line before every
class. Part of the material is covered in course
notes that are available online. For other topics
papers or notes will be made available. Several books are
also available for reference.
- Introduction [ppt]
- Geometry and Camera Model [ppt]
- Single View Metrology [ppt]
- Feature Matching and Tracking [ppt]
- Epipolar Geometry [ppt]
- Shape-from-Silhouettes [ppt]
- Stereo [ppt]
- Structured light and active ranging [ppt]
- Structure from motion [ppt]
- Self-calibration and Multi-View Geometry [ppt]
- see Changchang's webpage [link]