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Introduction to Robot Vision

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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Introduction to Robot Vision

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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.

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