Structured Light Camera Calibration for Distance Measurement Accuracy
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Solution Overview
Problem
Existing methods for identifying structural elements of a projected pattern in camera images face issues with accurate assignment due to distance and geometry variations, leading to incorrect distance measurements and potential safety hazards in monitoring danger zones.
Innovation Solution
A method and device that utilize precise calibration data to unambiguously associate structural elements in camera images with their projected counterparts, using calibration images to determine the position and orientation of cameras and a projector, allowing for correct distance measurement and safe zone assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If homogeneous point patterns are projected onto the scene, then less lighting energy is required and the pattern is sharply delimited, but points in camera images are often misassigned to the projected points leading to incorrect distance measurements
Solution Approach 1:
The patent applies preliminary action by performing calibration before actual measurement. Calibration images are captured at known positions to establish the relationship between camera images and projected pattern positions. This pre-established mapping data is then used during actual operation to correctly assign pattern points to camera image points, eliminating misassignment errors without requiring complex real-time calculations.
2Measurement precision
If more complex inhomogeneous aperiodic structural patterns are projected onto the scene to avoid incorrect assignment, then accurate distance measurement is improved, but equipment costs and projector complexity increase significantly
Solution Approach 1:
The patent uses preliminary calibration to establish mapping relationships between simple projected patterns and their positions in camera images. This pre-computed mapping data stored in calibration files allows the system to use simple homogeneous patterns during actual operation while maintaining accurate distance measurement, avoiding the need for complex aperiodic patterns.
Solution Approach 2:
The patent creates a virtual model (calibration data) that copies the geometric relationship between the projector, cameras, and scene. This virtual model is then used to interpret images from simple patterns, effectively replacing the need for physically complex patterns with computationally derived accuracy.
3Reliability
If calibration images are captured at multiple known positions to establish mapping relationships, then unambiguous assignment of structural elements is achieved, but calibration time and measurement time increase
Solution Approach 1:
The patent performs calibration in advance when the system is set up, capturing images at multiple known positions to build comprehensive mapping data. This one-time preliminary action establishes the geometric relationships that are then reused for all subsequent measurements, making the initial time investment worthwhile for ongoing operational accuracy.
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 reliable identification and assignment of structural elements, ensuring accurate distance measurement and safe operation of machines by reducing ambiguity and improving safety in monitored areas.
Implementation Method 1
a projector (36) for projecting a structure pattern (16) into the scene (14)
Implementation Method 2
a first camera (M) for capturing an image of the structure pattern (16) projected onto the scene (14), a second camera (H) for capturing an image of the structure pattern (16) projected onto the scene (14)
Implementation Method 3
An evaluation unit generates a depth map of the spatial area from the image data according to the stereoscopy principle
Data Source
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AI summary
In a method for identifying individual structural elements (12) of a structural pattern (16) projected onto a scene (14) in camera images, a projector (36) is used to project the structural pattern (16) onto the scene (14) and a first camera (M) and at least one second camera (H, V) are used to pick up the structural pattern (16) projected onto the scene (14). The first camera (M) and the at least one second camera (H; V) are positioned at a distance from one another, and the projector (36) is positioned at a distance from the first camera (M) and at a distance from the at least one second camera (H, V) outside a straight connecting line (26, 28) of the first camera and the at least one second camera (M, H, V). Calibration data which are obtained by recording calibration images (76, 78) of the structural pattern (16) projected by the projector (36) using the first camera and the at least one second camera (M, H, V) and in each case have, for the individual structural elements (12), combinations of first parameters, which correlate the particular structural element (12) with the position and orientation of the first camera (M) and the projector (36), and at least second parameters, which correlate the particular structural element (12) with the position and orientation of the at least one second camera (H, V) and the projector (36), are used to determine, for a structural element (12) to be identified in the camera image from the first camera (M), that structural element (12) in the camera image from the at least one second camera (V, H) which can be mutually clearly assigned to the structural element (12) to be identified in the camera image from the first camera (M).