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Introduction to Computer Vision PPT PDF Slides

Introduction to Computer Vision


Textbook

Readings will be assigned in "Computer Vision: Algorithms and Applications" by Richard Szeliski


Lecture Slides
Topic
Slides
Reading
Introduction to computer vision
Szeliski 1
Cameras and optics
Szeliski 2.1, especially 2.1.5
Light and color
Szeliski 2.2 and 2.3
Pixels and image filters
Szeliski 3.2
Thinking in frequency
Szeliski 3.4
Image pyramids and applications
Szeliski 3.5.2 and 8.1.1
Machine learning: overview

Machine learning: clustering
Szeliski 5.3
Machine learning: classification

Edge detection and line fitting w/ Hough transform
Szeliski 4.2
Robust fitting (Hough Transform)
Szeliski 4.3
Robust fitting (RANSAC and others)
Szeliski 4.3
Mixture of Gaussians and EM

Gestalt cues, MRFs, and graph cuts
Szeliski 5.5



Recoginition Overview and History
Szeliski 14
Image features and bag of words models
Szeliski 4.1.2, 14.4.1, and 14.3.2
Interest points: corners
Szeliski 4.1.1
Quiz 1


Interest points and instance recognition
Szeliski 14.3
Large-scale instance recognition
Szeliski 14.3.2
Detection with sliding windows
Szeliski 14.1
Guest talk: Jim Rehg, Behavior Imaging and the Study of Autism


Detection with sliding windows continued
Szeliski 14.2
Context and Spatial Layout
Szeliski 14.5
Guest talk: Gabriel Taubin, 3d photography


Feature Tracking
Szeliski 4.1.4
Optical Flow
see above
Szeliski 8.4
Guest lecture: Deqing Sun, Optical flow


Epipolar Geometry
Szeliski 11
Stereo Correspondence

Structure from Motion
Szeliski 7
Activity Recognition







Internet Scale Vision