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

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. Highly Efficient More advanced functions Pre-installed in Linux FC6 Inconsistent.

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

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  1. Stanford CS223B Computer Vision, Winter 2007Lecture 2b Software for Computer Vision Professors Sebastian Thrun and Jana Kosecka CAs: Vaibhav Vaish and David Stavens

  2. Matlab versus OpenCV Highly Efficient More advanced functions Pre-installed in Linux FC6 Inconsistent • Extremely easy to use • Interpreter + compiler • Advanced graphics • Difficult to install

  3. Matlab

  4. F1 - Matlab Help

  5. Basic Matrix Operations (Demo)

  6. Live Demo Here

  7. A Simple Example

  8. A Simple Example, Revisited • Check out Image Library, many common routines available

  9. Try “Image Toolbox Demos”

  10. Blurring Example Demo (1)

  11. Blurring Example Demo (2) • More steps in Matlab Demo

  12. Demo: Image Transformations

  13. Live Demo Here

  14. Matlab Code

  15. Matlab Code

  16. Output of edge_script.m

  17. Figure 4: quiver

  18. OpenCV by Gary Bradski, Intel

  19. OpenCV: Install as rpm

  20. OpenCV Code

  21. Compiling+Running OpenCV

  22. Movies in OpenCV:

  23. Live Demo Here

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