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

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


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

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

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