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Color Segmentation & Introduction to Motion Planning

Color Segmentation & Introduction to Motion Planning. CSE350/450-011 11 Sep 03. Administration. Questions?. Class Objectives. Review how color is represented and can be segmented in a computer image Introduction to basic Motion Planning for a mobile robot. Supporting References.

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Color Segmentation & Introduction to Motion Planning

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  1. Color Segmentation & Introduction to Motion Planning CSE350/450-011 11 Sep 03

  2. Administration • Questions?

  3. Class Objectives • Review how color is represented and can be segmented in a computer image • Introduction to basic Motion Planning for a mobile robot

  4. Supporting References • Color Segmentation • CVOnline “Color Image Processing” Lecture Notes • Poynton's Color FAQ • Motion Planning • “Motion Planning Using Potential Fields”, R. Beard & T. McClain, BYU, 2003

  5. Color Segmentation Motivation • Computationally inexpensive (relative to other features) • “Contrived” colors are easy to track • Combines with other features for robust tracking

  6. What is Color? • Color is the perception of light in the visible region of the spectrum • Wavelengths between 400nm - 700nm • Imagers • Retina (humans) • CCD/CMOS (cameras)

  7. RGB Color Space • Motivated by human visual system • 3 color receptor cells (rods) in the retina with different spectral response curves • Used in color monitors and most video cameras

  8. “Greyscale” Y= 0.30*R+0.59*G+0.11*B YCbCr (YUV/YIQ) Color Space • Separates luma (“brightness”) from the chroma (“color”) channels: Y = 0.30*R+0.59*G+0.11*B, Cb = B-Y, Cr=R-Y • YUV/YIQ are similar variants based upon NTSC/PAL television signals

  9. Representing Colors in an RGB Image Red Green Blue

  10. How do we segment a “single” color? Sample set for orange hat

  11. Simple RGB Color Segmentation Red Green Blue Again the Issue of Thresholding! Segmented Color Image & &

  12. Color Tracking Demo

  13. Motion Planning

  14. The Basic Motion Planning Problem Given an initial robot position and orientation in a potentially cluttered workspace, how should the robot move in order to reach an objective pose?

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