Stanford CS223B Computer Vision, Winter 2007 Lecture 2b Software for Computer Vision

transcript

Sebastian Thrun & Jana Kosecka CS223B Computer Vision, Winter 2007

Stanford CS223B Computer Vision, Winter 2007

Lecture 2b Software for Computer Vision

Professors Sebastian Thrun and Jana Kosecka

CAs: Vaibhav Vaish and David Stavens

Matlab versus OpenCV

• Extremely easy to use

• Interpreter + compiler

• Advanced graphics

• Difficult to install

• Highly Efficient

• More advanced functions

• Pre-installed in Linux FC6

• Inconsistent

Matlab

F1 - Matlab Help

Basic Matrix Operations (Demo)

Live Demo Here

A Simple Example

A Simple Example, Revisited

• Check out Image Library, many common routines available

Try “Image Toolbox Demos”

Blurring Example Demo (1)

Blurring Example Demo (2)

• More steps in Matlab Demo

Demo: Image Transformations

Live Demo Here

Matlab Code

Output of edge_script.m

Figure 4: quiver

OpenCV by Gary Bradski, Intel

OpenCV: Install as rpm

OpenCV Code

Compiling+Running OpenCV

Movies in OpenCV:

Live Demo Here

Documents