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Vision. The special sense by which the qualities of an object (as color, luminosity, shape, and size) constituting its appearance are perceived through a process in which light rays entering the eye are transformed by the retina into electrical signals that are transmitted to the brain via the optic nerve. [Miriam Webster dictionary].
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1. Introduction to Robot Vision
2. Vision The special sense by which the qualities of an object (as color, luminosity, shape, and size) constituting its appearance are perceived through a process in which light rays entering the eye are transformed by the retina into electrical signals that are transmitted to the brain via the optic nerve.
[Miriam Webster dictionary]
3. The Sensor
4. The Sensor
5. Machine Vision
6. Machine Vision
7. Machine Vision How hard can it be?
8. Machine Vision How hard can it be?
9. Robot Vision Simultaneous Localization and Mapping (SLAM)
Visual Servoing.
10. Robot Vision Simultaneous Localization and Mapping (SLAM) – create a 3D map of the world and localize within this map.
11. Robot Vision Simultaneous Localization and Mapping (SLAM) – create a 3D map of the world and localize within this map.
12. Robot Vision Visual Servoing – Using visual feedback to control a robot:
image-based systems: desired motion directly from image.
13. Robot Vision Visual Servoing – Using visual feedback to control a robot:
Position-based systems: desired motion from 3D reconstruction estimated from image.
14. Difficulty of similar tasks in different settings varies widely:
How many cameras?
Are the cameras calibrated?
What is the camera-robot configuration?
Is the system calibrated (hand-eye calibration)?
Common configurations: System Configuration
15. System Characteristics The greater the control over the system configuration and environment the easier it is to execute a task.
System accuracy is directly dependent upon model accuracy – what accuracy does the task require?.
All measurements and derived quantitative values have an associated error.
16. Stereo Reconstruction
17. Commercial Stereo Vision
18. Commercial Stereo Vision
19. Stereo Reconstruction
20. Camera Model
21. Camera Model
22. Camera Model
23. Camera Calibration
24. Camera Calibration
25. Obtaining the Rays Camera location in the calibration object’s coordinate system, C, is given by the one dimensional right null space of the matrix M (MC=0).
A 3D homogenous point P = M+p is on the ray defined by p and the camera center [it projects onto p, MM+p =Ip=p].
These two points define our ray in the world coordinate system.
As both cameras were calibrated with respect to the same coordinate system the rays will be in the same system too.
26. Intersecting the Rays
27. World vs. Model
28. Additional Material Code:
Camera calibration toolbox for matlab (Jean-Yves Bouguet ) http://www.vision.caltech.edu/bouguetj/calib_doc/
Machine Vision:
“Multiple View Geometry in Computer Vision”, Hartley and Zisserman, Cambridge University Press.
"Machine Vision", Jain, Kasturi, Schunck, McGraw-Hill.
Robot Vision:
“Simultaneous Localization and Mapping: Part I”, H. Durant-Whyte, T. Bailey, IEEE Robotics and Automation Magazine, Vol. 13(2), pp. 99-110, 2006.
“Simultaneous Localization and Mapping (SLAM) : Part II”,T. Bailey, H. Durant-Whyte, IEEE Robotics and Automation Magazine, Vol. 13(3), pp. 108-117, 2006.
“Visual Servo Control Part I: Basic Approaches”, IEEE Robotics and Automation Magazine, Vol. 13(4), 82-90, 2006.
Visual Servo Control Part II: Advanced Approaches”, IEEE Robotics and Automation Magazine, Vol. 14(1), 109-118, 2007.