3D Surface Acquisition via Multi-Sensor Fusion and Infrared Calibration
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Solution Overview
Problem
Current methods for acquiring three-dimensional representations of objects or scenes, particularly human subjects, face limitations such as sensitivity to ambient light, complexity in image fusion, and insufficient resolution, especially in applications like the clothing industry, where precise measurements are required.
Innovation Solution
An automated method and installation using a plurality of sensors and visual markers to calibrate and convert coordinates, allowing for precise and rapid acquisition of three-dimensional surfaces without additional light projection, with sensors projecting infrared patterns and providing depth and texture information, enabling real-time high-resolution data merging without mathematical processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single sensor is used with controlled movement, then device complexity is reduced, but measurement precision and acquisition quality deteriorate
Solution Approach 1:
The system divides the acquisition space into multiple zones, each covered by a dedicated sensor. Instead of using one sensor that must move to cover the entire space, multiple sensors are stationary and each captures a specific portion of the scene, eliminating the need for mechanical movement while maintaining high resolution.
Solution Approach 2:
Multiple sensors are combined to work simultaneously, each contributing to the overall 3D reconstruction. The sensors are synchronized to capture data at the same moment, and their individual measurements are merged through coordinate transformation to create a complete high-resolution model.
2Measurement precision
If multiple sensors are mounted on a support structure, then measurement precision is improved, but device complexity and calibration difficulty increase
Solution Approach 1:
A passive calibration object with known geometry is introduced as an intermediary element. This object is captured by all sensors during calibration, providing reference points that enable automatic computation of transformation matrices between sensor coordinate systems, eliminating manual calibration procedures.
Solution Approach 2:
The patent replaces manual mechanical calibration procedures with an automated computational approach. Transformation matrices are calculated algorithmically from captured images of the calibration object, substituting complex manual alignment and measurement processes with automatic image-based computation.
3Measurement precision
If structured light patterns are projected, then measurement precision is improved, but sensitivity to ambient light increases
Solution Approach 1:
The system uses periodic modulation of infrared light emission and synchronized detection. The infrared LED emits light in periodic pulses, and the sensor captures images at specific phases of this cycle, allowing differentiation between projected pattern light and ambient light through temporal synchronization.
Solution Approach 2:
The patent operates in an infrared wavelength regime that is effectively isolated from visible ambient light. By using infrared illumination and infrared-sensitive sensors, the system creates an optically inert environment where visible light does not interfere with measurements, eliminating sensitivity to ambient lighting conditions.
4Device complexity
If a single sensor captures the entire scene, then device complexity is reduced, but measurement precision deteriorates due to limited acquisition field
Solution Approach 1:
The acquisition space is segmented into multiple overlapping fields of view, each captured by a dedicated sensor positioned to optimize coverage of specific regions. This allows each sensor to operate at full resolution within its field while collectively covering the entire scene with high precision.
Solution Approach 2:
The system transitions from a single-point observation to a distributed multi-point observation network. By arranging sensors in three-dimensional space around the acquisition volume, the system achieves comprehensive coverage through spatial distribution rather than relying on a single sensor with extended range.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables easy, rapid, and precise automation of calibration, achieving high-quality three-dimensional surface acquisition and reconstruction with improved resolution and reduced sensitivity to ambient light, facilitating efficient data processing and merging of overlapping fields.
Implementation Method 1
one which projects a pattern or speckle of points in the non-visible (infrared) spectrum
Implementation Method 2
the three-dimensional image is reconstructed from at least two shots
Data Source
Figure 1A
Figure 1B
Figure 2A~2B
AI summary
The present invention relates to a method for the automatic acquisition, processing and digital restitution of several three-dimensional surfaces delimiting by cooperation an envelope of a physical body, in which the subject is placed in an acquisition space with sensor means and visual reference elements forming part of a corresponding installation.The method is characterized in that it consists of automatically carrying out a calibration phase of the installation (6), during which coordinate transformation matrices between each of the reference frames specific to the different sensors (4) and a single spatial reference frame associated with the installation (6) are calculated, and, for each new acquisition of three-dimensional surface representations by the different sensors (4), converting the voxel coordinates of said partial digital representations into the spatial reference frame associated with the installation (6) and constituting the complete three-dimensional representation of the envelope by orderly assembly of the different partial representations with fusion of said surfaces at the level of their mutually superimposed or overlapping peripheral areas.