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.

 

 

Latest News

 

 

 

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%