A virtual binocular three-dimensional reconstruction method based on structured light

Abstract

A virtual binocular three-dimensional reconstruction method based on structured light comprises the following steps: constructing a virtual binocular stereoscopic vision system, wherein the binocularstereoscopic vision system comprises a camera; calibrating the camera and obtaining the internal and external parameters of the camera; according to the internal and external parameters of the camera,obtaining the distortion mapping matrix; projecting regular structured light to the object to increase the surface texture of the reconstructed object; using the camera of binocular stereo vision system to capture the left and right images of the reconstructed object, and carrying out stereo correction on the images; extracting and matching the left image and the right image, and obtaining the parallax of the corresponding matching points on the left image and the right image with respect to the point P on the object; combining the internal and external parameters of the camera, and obtainingthe sparse three-dimensional coordinates of the object by using the parallax principle; according to the sparse three-dimensional coordinates of the object, generating the sparse point cloud image ofthe object, and completing the three-dimensional reconstruction of the object. The method is conducive to improving the accuracy and efficiency of three-dimensional reconstruction, and saves the cost.

Description

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AI Technical Summary

Benefits of technology

This technology combines two methods - Active Vision (AV) and Binocular Stereovision (BS). These techniques work together by adding special patterns onto objects' surfaces instead of just looking at them themselves without actually measuring their properties or shape. By doing this they enhance how well these things look like compared to previous technologies only showing what was previously possible. Additionally, it suggests creating an improved robot called BS that helps reduce errors during image processing and saves money when needed. Overall, this technology improves both precision and cost reduction over existing systems.

Problems solved by technology

This patented describes different ways to create accurate depth maps (BMs) during medical procedures such as surgery or dentistry. However, current techniques have limitations due to their lack of precision and efficient processability at small surfaces like teeth, gums, bone tissue, skin, muscle, blood vessels, nerves, cartilage, joint fluid, tendons, ligaments, spine structures, lungs, heart valves, brain stem cells, liver stones, kidneys, pancreas, urinary bladders, eye cornea, sclera, meniscus, pericardium, cardiovascular system components, neural networks, skeletal structure, connectivity between these systems, sensors, actuators, and other parts involved in biological processes involving human body movements. These technical problem addressed by this patents include improving the quality and consistency of BOM data used in various fields including medicine, science education, training simulations, industrial design, manufacturing, and analysis purposes.

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