Human body three-dimensional imaging method and system

Abstract

The invention is applicable to the field of three-dimensional imaging technology and provides a three-dimensional imaging method and system for the human body and a simultaneous calibration method for multiple control base stations. It achieves the calibration of all sensor structural parameters and their global matching parameters under the condition that the effective fields of view of each distributed sensor have no spatial overlap. The corresponding point search method that combines phase shift and random structured light is also used to reduce the image acquisition time for single-viewpoint depth data acquisition. The idea of ​​time multiplexing is also used to compress the overall data collection time of the system. At the same time, the design of distributed computing enhances the computing power of the entire system and improves the data acquisition speed. Based on calibrating the global matching parameters of different sensors, automatic matching of depth data from different sensors is achieved. The system is easy to debug and expand, has a high degree of automation and a simple 3D scanning process.

Description

technical field [0001] The invention belongs to the technical field of three-dimensional imaging, and in particular relates to a method and system for realizing three-dimensional imaging of a human body through distributed network control, and a simultaneous calibration method for multiple control base stations. Background technique [0002] Phase-assisted 3D imaging has the advantages of non-contact, fast speed, high precision, and high data density. It is widely used in industrial production fields such as reverse engineering, quality control, and defect detection. Generally, in industrial applications, a single 3D sensing system is used to achieve omnidirectional 3D imaging of objects through moving objects or sensing systems, which is often difficult to automate and takes too long. This solution is often difficult to apply to 3D imaging of human bodies. On the one hand, these human bodies have a large area and need to obtain 3D data from multiple angles; Quickly complet...

AI Technical Summary

Problems solved by technology

Generally, in industrial applications, a single 3D sensing system is used to realize omnidirectional 3D imaging of objects through moving objects or sensing systems, which is often difficult to automate and takes too long

This solution is often difficult to apply to 3D imaging of human bodies. On the one hand, these human bodies have a large area and need to obtain 3D data from multiple angles; Fast completion of 3D data acquisition

At present, the existing three-dimensional imaging systems of the human body mainly include: laser-based handheld and mechanical motion device scanning systems. The handheld imaging system realizes complete data collection through multi-angle hand-held movement, which usually takes a few minutes, during which the human body is difficult to maintain. Stationary; and imaging systems based on mechanical motion devices often require human body rotation or large mechanical motion control devices, which are bulky and cumbersome

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