Scene depth restoring and three dimension re-setting method for stereo visual system

Abstract

This invention relates to a method for recovering scene depth and re-building three-dimension of a stereoscopic vision system, which gets the inner parameters of right and left cameras, relative rotation matrix and shift vector by calibration, matching the corresponding points of the right and left images, evaluating the right and left normalization vectors of each pair of matched points from their image coordinates and relative inner parameters of the cameras, evaluating an equation of two projection lines from the center of the left camera to the left image point and from the center of the right camera to the right image point based on the coordinates and taking the depth value of the scene point in the coordinate systems of the two cameras as the parameter, evaluating the depth value and three-dimension coordinate of the common plumb end points of the two projection lines in the two camera coordinate systems by the normalized vector, the relative rotation matrix and the shift vector and evaluating the coordinate of the midpoint of the common plumb line from the coordinate of the two points of the line and takes the midpoint coordinate as the three-dimension one of the scene points to finish depth recovery and three-dimension restructuring.

Description

technical field [0001] The invention relates to a scene depth recovery and three-dimensional reconstruction method of a stereo vision system, in particular to a direct method for scene depth recovery and three-dimensional reconstruction from a stereo vision system with any configuration, which is suitable for scenes in computer vision and photogrammetry Depth restoration and 3D reconstruction. It belongs to the field of advanced manufacturing and automation. Background technique [0002] Stereo vision has been an important problem in computer vision and photogrammetry. A stereo vision system generally includes two or more cameras, and the internal parameters and relative positional relationship of these cameras become known data through calibration. The so-called scene depth recovery is to calculate the distance of a scene point relative to a certain camera along the main optical axis according to the corresponding image point coordinates of a scene point in two or more ca...

AI Technical Summary

Problems solved by technology

The second type of method usually requires initial value estimation first, and then iterative optimization, which is time-consuming and easy to converge to a local optimal solution, so it is rarely used in practical applications.

Therefore, the first type of method is generally used in stereo vision at present, but when using the first type of method, image correction needs to be performed first, which is also a time-consuming step, and errors will be generated during the transformation process of image correction, which will affect the reconstruction accuracy

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