3D Photography

Instructor: Prof. Dr. Marc Pollefeys

Assistant: Li Guan
Fall 2007

Lectures: Wed 9-11 ML H37.1

Exercices: Wed 11-12 ML H37.1

 

One of the key challenges in visual computing is to measure 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 project.  

 

Course Objectives

After attending this course students should:

  1. Understand the concepts that allow recovering 3D shape from images.
  2. Have a good overview of the state of the art in 3D photography
  3. Be able to critically analyze and asses current research in the area
  4. Implement components of a 3D photography system.

 

Course Topics
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.

 

Target Audience
The target audience of this course are Master or PhD students, or advanced Bachelor students, that are interested in learning about 3D photography and related topics.  


Learning Approach

  • In the first part of the class the main 3D photography 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 state-of-the-art. 
  • Students will implement components of a 3D photography system as a course project.

 

Prerequisites
The course is open to all students that have taken an introductory course in computer vision or computer graphics, or have equivalent background.  Students that are not sure if they satisfy the prerequisites should contact the instructor.

 

Course Notes
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.


Slides

  • Class 1 Introduction [ppt]
  • Class 2 Geometry and camera model [ppt]
  • Class 3 Single View Metrology [ppt]
  • Class 4 Feature Matching and Tracking [ppt]
  • Class 5 Epipolar Geometry [ppt]
  • Class 6 Silhouette-based reconstructions [ppt]
  • Class 7 Stereo matching [ppt]
  • Class 8 Structured light [ppt]
  • Class 9 Structure from motion [ppt]
  • Class 10 Self-calibration and multi-view geometry [ppt]
  • Class 11 Shape-from-X [ppt]

Exercises

See Li Guan's webpage [link]

(below, old slides from fall 2004, will be updated)

(check out the video of Class 1 to get an overview of the course and applications)

  • Class 1 Introduction [ppt][video]
  • Class 2 Projective geometry [ppt]
  • Class 3 Camera model and calibration [ppt]
  • Class 4 Camera calibration and single view metrology [ppt]
  • Class 5 Feature matching [ppt]
  • Class 6 Feature tracking [ppt]
  • Class 7 Epipolar Geometry [ppt]
  • Class 8 Computing F [ppt]
  • Class 9 Triangulation and Multiple View Geometry [ppt]
  • Class 10 Stereo [ppt]
  • Class 11 Structured light and active ranging [ppt]
  • Class 12 Structure and motion recovery [ppt]
  • Class 13 Self-calibration [ppt]
  • Class 14 Shape from silhouettes [ppt]
  • Class 15 Space carving [ppt]
  • Class 16 3D reconstruction [ppt]
  • Class 17 Appearance modeling [ppt]


Marc Pollefeys, last updated November 7, 2007.