The calendar/syallbus for the class taught in Fall 2014 is here. This has the slides from the lectures given in class.
Key:
FP: Forsyth and Ponce, Computer Vision: A Modern Approach (2nd
edition)
Sz: Szeliski, Richard Computer Vision: Algorithms and Applications
Wk |
Lecture |
Text ch, pgs |
Assignments |
1 |
Intro |
Sz: 1.1,1.2 |
P0: Image
basics |
|
Matlab tutorial |
|
|
2 |
Linear
Filtering/Convolution |
FP: 4 (all) |
P1: Edges
and Hough transform |
|
Edges
and Lines |
FP: 5.1, 5.2 |
|
3 |
Hough
Transform and Shapes |
FP: 10.1 |
|
|
Frequency |
FP: Chap 4 |
|
4 |
Aliasing
|
FP: Chap 4 |
|
|
Camera
Models |
FP: 1, 2.1-2.2 |
P2: Stereo
matching |
5 |
Stereo - Matching |
FP: Chap 7 |
|
|
Camera
Calibration |
FP: Chap 8 |
|
6 |
Two
Views (1) |
FP: Chap 7.1, 8 (all) |
|
|
|
|
|
7 |
Two
Views (2) |
|
P3:
Calibration |
|
Harris
Corners |
FP: 5.3-5.4, |
|
8 |
SIFT |
FP 5.4; Sz: 4.1 |
|
|
RANSAC |
FP 10.2-10.4 |
|
9 |
|
|
|
|
Photometry
|
FP 2.1-2.2 |
P4: Harris,Sift,Ransac |
10 |
Segmentation |
FP: 9 |
|
|
Motion
and Optic Flow |
FP 10.6 |
|
11 |
Motion
Models and Pyramids |
|
|
|
Tracking
1- Kalman |
FP 11.3 |
P5: Motion and flow |
12 |
Tracking
2 – Particle filters |
FP 11.5 |
|
|
PCA |
FP 16.1.5 |
|
13 |
Classification - Generative |
FP
15.1-15.2 |
|
|
Classification - Discriminative |
|
P6: Tracking |
14 |
Classification
- BOW |
|
|
|
Hidden Markov Models |
FP 20.1 |
|
15 |
Activity
Recognition |
|
P7: MHIs |
|
|
||
16 |
Morphology;
Depth Sensing |
|
|
|
Human
Vision |
|
|