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Instructor: David B. Cooper Office: Barus & Holley Room 318 Phone: 863-2601 E-mail: cooper@lems.brown.edu
Fall, 2005-2006 Undergraduate/beginning Graduate Level Mon, Wed, Fri 2:00-2:50 (G Hour)
Laboratory Sessions Links to previous years web pages: 1999 - 2000 - 2001 - 2002 - 2003 - 2004
This course is designed for both undergraduate and graduate students in Engineering, Applied Mathematics, Computer Science, Cognitive Science, and Neuroscience, who have some knowledge of advanced calculus, Fourier series, and some MATLAB programming.
The goals of the course are to understand camera image-formation and image properties, and to learn and use some concepts and algorithms for the extraction of useful image features and features of the 3D scene being imaged. Among the broad topics to be covered are: Geometric and radiometric camera models for image formation; Properties of points, lines and curves in 2 and 3 dimensions, and how they transform under motion and viewing; Linear and nonlinear image enhancement, filtering and compression; Elementary statistical estimation and detection and application to edge detection, object boundary estimation, texture representation and region segmentation, and object recognition; invariants – properties of points lines and curves that remain invariant under transformations (useful for object recognition); stereo vision (3D surface and geometry reconstruction from multiple images). Fun MATLAB assignments will illustrate concepts and algorithms, and short student-presentations of journal papers at the end of the semester will further illustrate applications.
Texture Estimation / Inpainting
Face Detection / Biometrics
Morphological Filtering / Skeletonization
Edge Detection / Tracking
