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Surveillance and Security

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Project Industrial site Monitored by two cameras

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Camera Calibration Thomas Flamant

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Goal 4Calibration Camera Calibration Camera matrix Reconstruction get_mapped.m (WP3)

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Camera Calibration (Camera resectioning) 5Calibration = the process of finding the true parameters of the camera that produced a given photograph or video Pinhole camera model Camera matrix Represents the camera parameters

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Pinhole camera model 6Calibration Describes the mathematical relationship between the coordinates of a 3D point and its projection onto the image plane of an ideal pinhole camera

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Camera matrix 7Calibration Describes the mapping of a pinhole camera from 3D points in the world to 2D points in an image. Intrinsic parametersExtrinsic parameters

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Intrinsic Parameters (intrinsic calibration) 8Calibration

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Extrinsic Parameters (extrinsic calibration) 9Calibration

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Camera matrix 10Calibration Describes the mapping of a pinhole camera from 3D points in the world to 2D points in an image. Intrinsic parametersExtrinsic parameters

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Camera matrix 11Calibration Describes the mapping of a pinhole camera from 3D points in the world to 2D points in an image. Intrinsic parametersExtrinsic parameters

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Camera matrix 12Calibration Describes the mapping of a pinhole camera from 3D points in the world to 2D points in an image. Intrinsic parametersExtrinsic parameters

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Camera matrix 13Calibration Describes the mapping of a pinhole camera from 3D points in the world to 2D points in an image. Intrinsic parametersExtrinsic parameters (Bouguet) (POSIT)

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Camera Calibration Toolbox for Matlab (Bouguet) Input: 20+ images of a planar checkerboard Output: Intrinsic parameters Corner extraction Automatic: RADOCC Camera Calibration Toolbox (CornerFinder.m) 14Calibration

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Camera Calibration Toolbox for Matlab (Bouguet) Input: 30 images of each camera (squares = 28mm) Camera 1: Camera 2: 15Calibration

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Camera Calibration Toolbox for Matlab (Bouguet) 16Calibration Input: 30 images of each camera (squares = 28mm) Camera 1: Camera 2:

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Camera Calibration Toolbox for Matlab (Bouguet) Output: intrinsic parameters of each camera Camera 1: Camera 2: 17Calibration

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POSIT Description: POSIT is a fast iterative algorithm for finding the pose (rotation and translation) of an object or scene with respect to a camera when points of the object are given in some object coordinate system and these points are visible in the camera image and recognizable, so that corresponding image points and object points can be listed in the same order. [rotation, translation] = Posit(imagePoints, objectPoints, focalLength, center) 18Calibration

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POSIT Input: nbPts : 4+ noncoplanar feature points of the object imagePoints : matrix of size nbPts x 2 objectPoints : matrix of size nbPts x 3 focalLength : focal length of the camera in pixels Center : row vector with the elements of the image center 19Calibration [rotation, translation] = Posit(imagePoints, objectPoints, focalLength, center) Camera 2

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POSIT Input: nbPts : 4+ noncoplanar feature points of the object imagePoints : matrix of size nbPts x 2 objectPoints : matrix of size nbPts x 3 focalLength : focal length of the camera in pixels Center : row vector with the elements of the image center Output: rotation : 3 x 3 rotation matrix of scene with respect to camera translation : 3 x 1 translation vector from projection center of camera to FIRST POINT in list of object points 20Calibration [rotation, translation] = Posit(imagePoints, objectPoints, focalLength, center)

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Output: extrinsic parameters of each camera Camera 1: Camera 2: 21Calibration POSIT

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Camera matrix 22Calibration Describes the mapping of a pinhole camera from 3D points in the world to 2D points in an image. Intrinsic parametersExtrinsic parameters (Bouguet) (POSIT)

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Camera matrix 23Calibration Describes the mapping of a pinhole camera from 3D points in the world to 2D points in an image. Camera 1: Camera 2:

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Goal 24Calibration Camera Calibration Camera matrix Reconstruction get_mapped.m (WP3)

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Reconstruction 25Calibration 3D-reconstruction: Triangulation 2D-reconstruction: Calibration matrix

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3D-reconstruction (Triangulation) 26Calibration Epipolar geometry: When two cameras view a 3D scene from two distinct positions, there are a number of geometric relations between the 3D points and their projections onto the 2D images that lead to constraints between the image points.

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3D-reconstruction (Triangulation) 27Calibration Triangulation: The process of determining a point in 3D space given its projections onto two, or more, images. In order to solve this problem it is necessary to know the parameters of the camera projection function from 3D to 2D for the cameras involved, represented by the camera matrices

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2D-reconstruction (Calibration matrix) 28Calibration 3 dimensions ? Camera 2

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2D-reconstruction (Calibration matrix) 29Calibration 2 dimensions ! Camera 2

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2D-reconstruction (Calibration matrix) 30Calibration 2 dimensions ! Camera 2

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2D-reconstruction (Calibration matrix) 31Calibration 2 dimensions ! Camera 2

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2D-reconstruction (Calibration matrix) 32Calibration 2 dimensions ! Function get_mapped.m WP3 function [ x_world, y_world ] = get_mapped(camera_nr, x_pixel, y_pixel)

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Motion detection Hannes Van De Vreken

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Person detection Jan Heuninck

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Demonstration