Foundations of Image Science

Pascal Fua

Course summary

Advanced classes in the fields of Digital Photography, Computer Vision, and Computer Graphics require the mastery of a certain number of mathematical techniques and of their actual implementations. This course aims at supplying this knowledge by combining formal lectures and software development and prototyping exercises under JAVA.

Course outline

Image Geometry and Radiometry

• Cameras and projective geometry
• Light sources, shadows and shading
• Measuring and sampling light
• Color and Texture

Image Filtering and its Applications

• Linear Filters
• Convolution and separability
• Fourier Transform
• Edge and Texture Detection

Discrete Optimization

• Dynamic programming and edge linking
• Graph cuts and segmentation

Textbooks

• D. A. Forsyth, J. Ponce, Computer Vision: A Modern Approach, Prentice Hall, 2002.
• R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, Cambridge University Press, 2003.

Lecture notes

Image Geometry and Radiometry

• Image Formation
• Perspective camera model
• Projective geometry in 2 and 3D
• Parameter Estimation and Calibration
• Illumination
• Color

Image Filtering and its Applications

• Linear filters
• Fourier transform

Application

• Video-based tracking

Exercices and Projects

• Exercises every other week
• Semester and diploma projects

Demonstrations on the Web

Interpolation and information loss

Stereo from a single image

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