These class notes can be found at
http://www-prima.imag.fr/Prima/jlc/Courses/2010/GVR.VO/GVR-VO.html
The Physics of Light
The Human Visual System
Color Spaces and Color Models
Early Methods for Edge Detection: Roberts and Sobel
Image Derivatives: A modern view on contrast
Binomial Smoothing
Measuring contrast with smoothed difference filters
The Hough Transform
Second Derivatives and the Laplacian Operator
Describing Local Appearance
The Sampled Gaussian Functions
Gaussian Derivative
Operators
Properties Gaussian Derivative
Operators
Using the Gaussian to compute image
derivatives
21 October 2010 Lesson 4 - Open CV
Invariant Image description
Image Scale
Scale Invariant Pyramid Algorithm
Scale Invariant Interest Points
12 November 2010 No Class
Invariant Image Description
Histogram of
Gradients
Natural
Interest Points
SIFT
Integral Images
SURF
Bayesian
Recognition
Classification by Ratio of Histograms of pixel values
Face Detection
with Cascade of
Classifiers
25 November 2010 Midterm exam
02 December 2010 Lesson 7 Projective Geometry (Edmond Boyer)
09 December 2010 Lesson 8 Structure From Motion (Edmond
Boyer)
16 December 2010 Lesson 9 Reconstruction (Edmond Boyer)
06 January 2011 Lesson 10 3D Shape Modeling (Edmond Boyer)
13 January 2011 Lesson 11 Motion Models,
Articulated Motion (Edmond Boyer)
20 January 2011 Lesson 12 Action Recognition (Edmond
Boyer)
Past Exams
M2R GVR 2009: Computer Vision Exam from November
2009
M2R GVR 2008: Computer Vision Exam from
January 2009