290A - Topics in CS: Computational Photography and Video
Lectures: Mondays and Wednesdays 3:25-4:40 CSB 632


Course Description
This course will cover computational aspects of image, video processing and interactive photography. Topics will be selected from: imaging and low level image processing, compression, video processing and tracking, image segmentation, combining / compositing images, stereo vision, depth and 3D reconstruction techniques, image registration, face detection and recognition, general object recognition, image and video indexing and retrieval. Real world examples will be drawn from commercial, artistic, medical and scientific applications. Prerequisites: MTH 165; CSC 242 recommended but not required.
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Syllabus
|
# |
Date |
Topics |
|
|
1 |
September |
Wed. 5 |
Introduction, course overview & history (.pdf of handouts) |
|
2 |
Mon.10 |
Light and Image formation |
|
|
3 |
Wed.12 |
Image sensors & low level processing |
|
|
4 |
Mon.17 |
Color and perception |
|
|
5 |
Wed.19 |
High dynamic range imaging |
|
|
6 |
Mon. 24 |
Wavelets, pyramids and texture |
|
|
7 |
Wed.26 |
Image compression and Assignment #1 hand out |
|
|
8 |
October |
Mon. 1 |
Traveling - Cornell. (Quiz ) |
|
9 |
Wed. 3 |
Introduction to probability models |
|
|
10 |
Mon. 8 |
Fall break |
|
|
11 |
Wed 10 |
Probability models part II |
|
|
12 |
Mon. 15 |
Density estimation and classification |
|
|
13 |
Wed. 17 |
Markov random fields and segmentation |
|
|
14 |
Mon. 22 |
Image compositing and matting |
|
|
15 |
Wed. 24 |
Image registration 1: introduction - aerial, consumer, medical |
|
|
16 |
Mon. 29 |
Image registration 2: geometry and 3D |
|
|
17 |
Wed. 31 |
3D Medical image reconstruction |
|
|
18 |
November |
Mon. 5 |
Dense stereo methods |
|
19 |
Wed. 7 |
Interest point detectors and Assignment #2 hand out |
|
|
20 |
Mon. 12 |
Feature descriptors |
|
|
21 |
Wed. 14 |
Bundle Adjustment |
|
|
22 |
Mon. 19 |
Object recognition I |
|
|
23 |
Wed. 21 |
Thanksgiving break |
|
|
24 |
Mon. 26 |
Object recognition II |
|
|
25 |
Wed. 28 |
Face detection and recognition |
|
|
26 |
Dec. |
Mon. 3 |
Features and video processing |
|
27 |
Wed. 5 |
Last class: Project presentations |
|
|
28 |
Mon. 10 |
Last class: Project presentations |
|
|
29 |
Wed. 12 |
Video Search |
|
Additional Readings
Select chapters of Numerical Recipes in C:
3.1 Polynomial Interpolation and Extrapolation
3.3 Cubic Spline Interpolation
12.0 Introduction
12.1 Fourier Transform of Discretely Sampled Data
12.2 Fast Fourier Transform (FFT)
12.3 FFT of Real Functions, Sine and Cosine Transforms
13.1 Convolution and Deconvolution Using the FFT
13.2 Correlation and Autocorrelation Using the FFT
13.10 Wavelet Transforms
Tentative Grading Scheme
|
Component |
% |
|
Assignment #1 |
20% |
|
Assignment #2 |
20% |
|
Tests (2) |
30% |
|
Project |
30% |