3D Feature Point Calibration Using Visible Reference Pointers
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Solution Overview
Problem
Existing methods for determining the coordinates of feature points in 3D space, particularly for invisible objects within a vehicle's interior, are slow, error-prone, and require tedious manual measurements, making them inefficient for calibrating 3D gesture recognition systems.
Innovation Solution
A method involving the use of dedicated pointers arranged in a predetermined relation to the feature point, with visible features captured by a camera, allowing the determination of the feature point's coordinates based on the visible features' known positions and their relation to the invisible point.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual measurement methods are used to determine coordinates of invisible feature points, then measurement can be performed, but the process is slow and error-prone
Solution Approach 1:
The patent introduces dedicated pointers as intermediary objects that connect visible and invisible feature points. These pointers have known spatial relationships to target feature points and contain visible features that can be detected by the camera. By detecting the pointer's visible features and using the predetermined spatial relationship, the system indirectly determines coordinates of invisible feature points, resolving the contradiction between measurement accuracy and calibration efficiency.
Solution Approach 2:
The dedicated pointers serve as physical copies or representations of the invisible feature points, with known geometric relationships. Instead of directly measuring inaccessible feature points, the system measures the pointer's visible features and mathematically derives the target coordinates through the predetermined spatial relationship, achieving both accuracy and efficiency.
2Loss of information
If all feature points of an object are directly measured, then complete object representation is achieved, but measurement time and complexity increase significantly
Solution Approach 1:
The patent extracts only the essential information needed for object representation by using dedicated pointers that encode the spatial relationship between visible and invisible feature points. Instead of measuring all feature points directly, the system extracts coordinates of invisible points through mathematical derivation from pointer measurements, maintaining information completeness while reducing measurement time.
3Productivity
If dedicated pointers with visible features are used to represent invisible feature points, then calibration efficiency improves, but system complexity increases
Solution Approach 1:
The patent segments the calibration task into two parts: (1) detecting visible features of dedicated pointers using the existing camera system, and (2) calculating invisible feature point coordinates through predetermined spatial relationships. This segmentation allows the use of simple, existing hardware while achieving efficient calibration, as the complexity is managed through software algorithms rather than additional hardware.
Data Source
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AI summary
A method for determining a coordinate of a feature point of an object in a 3D space comprises: arranging at least one dedicated pointer in the 3D space in a pre-determined relation to the feature point of the object in the 3D space, wherein each dedicated pointer has at least one visible feature in line of sight of the camera; capturing at least one image by using the camera; performing image feature detection on the at least one captured image to determining a coordinate of the respective at least one visible feature of each dedicated pointer; and determining the coordinate of the feature point of the object in the 3D space based on the determined coordinate of the respective at least one visible feature of each dedicated pointer.