Lectures
Date  Lecture Description  Readings  Homework / Assignments  Materials / Announcements 
Jan 2008  Computer Vision History  Lecture note 1  
Jan 2008  Measurement of Motion:

Lecture note 2  Form groups for course project.  
17 Jan 2008  Displacement Models

Lecture note 3  Homework 1  OpenCV
Instructions OpenCV Examples Fundamental Matrix Example 
21 Jan 2008 
Computing Optical Flow

Lecture note 4  
23 Jan 2008 
Pyramids

Lecture note 5  Lucas Kanade code in MATLAB  
28 Jan 2008 
Global Flow

Lecture note 6  Homework 2 (due 4 Feb)  
30 Jan 2008 
Video Mosiac  Lecture note 7  
4 Feb 2008 
Featurebased Registration  Lecture note 8  1 Homework 3 (due 11 Feb) 2 Program Assignment (due 18 Feb) 3 Wide Baseline Matching Lecture 
Associated Files: seq1 seq2 seq3 head Imgs 
6 Feb 2008  Target Tracking Using Mean Shift  Lecture note 9  
11 Feb 2008 
Change Detection Skin Detection 
Lecture note 10  
13 Feb 2008 
Structure from Motion  Lecture
note 11 Lecture note 100 
Programming assignment 1 Presentations (18 Feb)  
18 Feb 2008 
Modelbase Video Compression  Lecture note 12  
20 Feb 2008 
Recognizing Facial Expressions  Lecture note 13  
24 Feb 2008 
Kalman Filter  Lecture note 14  Homework 4 (due 24 Mar)  
26 Feb 2008 
Hand Gesture Recognition  Lecture note 15  
1 Mar 2008 
Lecture note 16  
3 Mar 2008 
Action Recognition  Lecture note 17  
17Mar 2008 
Multi View Geometry of Moving Cameras  Lecture note 20  Mid Term Exam: Wednesday April 16  
24 Mar 2008 
Classification of Video Shots Using 3D Camera Motion  Lecture note 30 
March 31: Questions/answers Lecture 210…. (point out the errors/typos in the slides) April 2: Questions/answers Lecture 1114 (Kalman filter ) and Lecture 100 (point out the errors/typos in the slides) 
Syllabus
Displacement Models
Computing Optical Flow
Pyramids
Global Flow
Video Mosiac
Featurebased Registration
Target Tracking Using Mean Shift
Change Detection
Skin Detection
Structure from Motion
Modelbase Video Compression
Recognizing Facial Expressions
Kalman Filter
Hand Gesture Recognition
Action Recognition
Grading Policy
 Homeworks 15%
 Midterm exam 15% (Wednesday April 16)
 Project 70%
Homeworks and Assignments
 Show (1), (2) and (3) in lecture note 3.
 Experiment with five different openCV routines
 Experiement with five different openCV routines on video.
 Show proof for Bilinear interpolation in slide 48 of lecture note 5.
 Show (a), linear system equation in Anandan’s method, in slides 8 and 9 of lecture note 6.
 (b) Derive equations for Mann’s method (weighted) Lecture 7, page 5 top slide.
 (c) Derive equations for Mann’s method (unweighted) Lecture 7, page 10 top slide.
 (a) Drive Optical flow equation in page 81 of lecture note 12 (21 of handouts).
 (b) Drive equation of Planar Patch in page 85 of lecture note 12 (22 of handouts).
 (c) Drive equation of error function in page 81 of lecture note 12 (21 of handouts).
 Group (a)
Implement Anandan’s algorithm using affine transformation. To show the results generate a mosaic.  Group (b)
Implement Szeliski’s algorithm using projective transformation. To show the results generate a mosaic.  Group (c)
Implement Mann’s algorithm using projective transformation. To show the results generate a mosaic.
Implement all four steps:  Pyramid construction
 Motion estimation
 Image warping
 Coarsetofine refinement
Porjects
Some notes about project:
Since it is 70% of your grade, it will require significant amount of effort. It will require at least three times the effort you put in on the program..
Project can deal with the real world system, which can demonstrate some new and interesting application of computer vision.. (Applications project)
Project can be on completely new idea, which can ultimately become a research paper, but the paper is not expected for the class. (research project)
Project should not be just implementation of some paper..
Project should demonstrate understanding of concepts which you have learnt in the class, or other concepts which you have not learnt, but need to learn in order to finish the project.
Please seek help from me for the project…
Initial ideas are always important, but preliminary, they need to be refined… I can help you to refine these, you need to be willing to put in efforts…
Week of March 24
March 26 No class; Attend Talk by Professor Zhu at 4:00 PM, Harris 101
Week of April 7 (15% of your grade)
April 7 Demo/Report for Term Project (four students: Bilal, Ramin, Kagin, Yan)
April 9 Demo/Report for Term Project (four students; Yusuf, Enrique, Suraj, Abassel)Week of April 14
April 14 Exam (15% of your grade)
April 16 Lecture on Facial expression Recognition
Week of April 21 (15% of your grade)
April 21 Demo/Report for Term Project (four students: Bilal, Ramin, Kagin, Yan)
April 23 Demo/Report for Term Project (four students; Yusuf, Enrique, Suraj, Abassel)
Final exam April 28?
Demos of your projects: Open to public ..