CS 378 Computer Vision

Fall 2009

Syllabus overview

I. Features

• Linear filters
• Edge detection
• Binary image analysis
• Image pyramids
• Texture

II. Grouping and fitting

• Fitting lines and curves
• Robust fitting, RANSAC
• Hough transform
• Segmentation
• Clustering

III. Cameras and multiple views

• Camera models, image formation
• Planar homography
• Image warping
• Epipolar geometry
• Stereo
• Camera calibration
• Invariant local features

IV. Recognition and learning

• 2D recognition
• Bags of words representations
• Feature indexing and pose verification
• Shape matching
• Nearest neighbors
• Support vector machines
• Boosting

V. Motion and tracking

• Optical flow
• Tracking
• Video analysis