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COMP 150: Developmental Robotics Instructor: Jivko Sinapov www.cs.tufts.edu/~jsinapov This Week Theories of Vision Computer Vision Human Vision Project Breakouts Annoucements New reading assignment Thanks for the feedback!


  1. COMP 150: Developmental Robotics Instructor: Jivko Sinapov www.cs.tufts.edu/~jsinapov

  2. This Week ● Theories of Vision – Computer Vision – Human Vision ● Project Breakouts

  3. Annoucements ● New reading assignment

  4. Thanks for the feedback! ● Overall you seemed happy ● Many wished for more hands-on work with the robots ● “the 2 cool robot kids in the back”

  5. What is an image?

  6. A grayscale image

  7. An RGB image

  8. How did computer vision start? In 1966, Marvin Minsky at MIT asked his undergraduate student Gerald Jay Sussman to “spend the summer linking a camera to a computer and getting the computer to describe what it saw”. We now know that the problem is slightly more difficult than that!

  9. Computer vision vs human vision What we see What a computer sees

  10. Intensity Levels • 2 • 32 • 64 • 128 • 256 (8 bits) • 512 • … • 4096 (12 bits)

  11. Intensity Levels • 2 • 32 • 64 • 128 • 256 (8 bits) • 512 • … • 4096 (12 bits)

  12. Image Plane v.s. Image Array [Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 1]

  13. Point Operations [Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 1]

  14. Local Operations [Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 1]

  15. Global Operations [Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 1]

  16. Thresholding an Image [Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 1]

  17. Dark Image on a Light Background [Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 2]

  18. Selecting a range of intensity values [Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 2]

  19. Generalized Thresholding [Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 2]

  20. Thresholding Example (1) [Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 2]

  21. Thresholding Example (2) Original grayscale Image [Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 2]

  22. [Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 2]

  23. [Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 2]

  24. Color

  25. The RGB Color Space [http://www.arcsoft.com/images/topics/darkroom/what-is-color-space-RGB.jpg]

  26. The RGB Color Space https://upload.wikimedia.org/wikipedia/commons/thumb/1/11/RGBCube_b.svg/2000px-RGBCube_b.svg.png

  27. 3D Scatter Plot for a patch of skin

  28. The HSV Color Space

  29. Color Detection and Segmentation

  30. Discussion: how may we achieve this?

  31. Example Hand Tracking using Color

  32. Motion

  33. What is this?

  34. What is this?

  35. Bobick, Aaron F. "Movement, activity and action: the role of knowledge in the perception of motion." Philosophical Transactions of the Royal Society of London B: Biological Sciences 352.1358 (1997): 1257- 1265.

  36. Motion Energy Image (MEI) [http://www.cse.ohio-state.edu/~jwdavis/CVL/Research/MHI/mhi.html]

  37. Average MEI for various viewing angles

  38. Motion History Image (MHI) [http://www.cse.ohio-state.edu/~jwdavis/CVL/Research/MHI/mhi.html]

  39. Definitions ● Image Sequence ● Binary Images indicating regions of motion ● Binary Motion Energy Image

  40. Motion Energy

  41. Motion History The result: more recently moving pixels appear brighter

  42. [http://www.cse.ohio-state.edu/~jwdavis/CVL/Research/MHI/mhi.html]

  43. Motion templates for finishing LEFT-ARM-RAISE and FAN-UP-ARMS. [http://www.cse.ohio-state.edu/~jwdavis/CVL/Research/VirtualAerobics/aerobics.html]

  44. Aerobics Dataset

  45. Video

  46. A. Bobick, S. Intille, J. Davis, F. Baird, C. Pinhanez, L. Campbell, Y. Ivanov, A. Schutte, and A. Wilson (1999) ``The Kidsroom: A Perceptually-Based Interactive and Immersive Story Environment" Presence: Teleoperators and Virtual Environments, Vol. 8, No. 4, 1999, pp. 367-391.

  47. The Kid’s Room [Bobick et al. 1996]

  48. The Blue Monster [http://vismod.media.mit.edu/vismod/demos/kidsroom/kidsroom.html]

  49. The Technology [http://vismod.media.mit.edu/vismod/demos/kidsroom/kidsroom.html]

  50. Motion History Templates Making a ‘Y’ Flapping Spinning [http://vismod.media.mit.edu/vismod/demos/kidsroom/kidsroom.html]

  51. Detecting the Bed [http://vismod.media.mit.edu/vismod/demos/kidsroom/kidsroom.html]

  52. Man Overboard Detector [http://vismod.media.mit.edu/vismod/demos/kidsroom/kidsroom.html]

  53. C++ Computer Vision Libraries ● OpenCV: – http://wiki.ros.org/vision_opencv – http://wiki.ros.org/cv_bridge/Tutorials – http://docs.opencv.org/2.4/doc/tutorials/tutorials.html ● Point Cloud Library: – http://pointclouds.org/

  54. Project Breakout ● Identify your next steps… ● Identify and find the tools that you need – e.g., simulators, open-source libraries, datasets, etc. ● Break up the problem into parts so that you can work on them in parallel ● Design your pipeline – what goes in and what goes out and what happens in between

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