Global optimal registration method of multi-viewpoint cloud data during optical three-dimensional measurement
A technology of three-dimensional measurement and global optimization, which is applied in the direction of measuring devices, image data processing, and optical devices, etc., can solve the problems of measurement deviation of public marking points, etc., and achieve a small amount of calculation, unlimited measurement range, and high reliability. Effect
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specific Embodiment approach 1
[0024] Specific implementation mode one: the following combination figure 1 This embodiment will be specifically described. A global optimization registration method for multi-view point cloud data in optical three-dimensional measurement, the method is based on a hardware system platform including an acquisition device and a computer control device, marking points are pasted on the object to be measured as characteristic mark points of the object to be measured, and the computer The control device controls the acquisition device to collect the measurement data information of the object to be measured from N viewpoints respectively, obtains two-dimensional measurement data of N groups of objects to be measured, extracts the two-dimensional measurement data of N groups of characteristic mark points of the object to be measured, and converts them to Restoring the three-dimensional measurement data of N groups of feature marker points of the object to be measured, wherein N is th...
specific Embodiment approach 2
[0040] Embodiment 2: This embodiment is a further limitation of the global optimization registration method for multi-view point cloud data in optical three-dimensional measurement described in Embodiment 1, and the acquisition device is a CCD camera.
specific Embodiment approach 3
[0041] Specific embodiment three: this embodiment is a further limitation of the global optimal registration method for multi-view point cloud data in optical three-dimensional measurement described in specific embodiment one. In step one, the rotation matrix described is a 3×3 matrix, the translation vector is a 3×1 vector, the unit quaternion is a 4×1 vector, and the coordinate transformation vector composed of the unit quaternion and the translation vector is a 7× A vector of 1.
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