Coded Light Pattern for 3D Shape Capture
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Solution Overview
Problem
Current three-dimensional imaging systems using active triangulation methods are limited in capturing dynamic objects due to the need for multiple light patterns and are prone to errors in feature identification and precision, especially when objects are in motion.
Innovation Solution
A method and system that utilize a coded light pattern with unique bi-dimensional formations projected onto objects, allowing for the extraction of reflected features along epipolar lines to determine 3D spatial coordinates, enabling accurate 3D shape and motion capture of both static and moving objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple light patterns are projected onto objects to capture dynamic objects, then the ability to capture moving objects is improved, but the complexity of the system and the time required for acquisition increase
Solution Approach 1:
The light pattern is segmented into multiple distinguishable feature types (e.g., different shapes, sizes, orientations of geometric features) that can be independently identified. This segmentation allows the system to track multiple features simultaneously within a single projected pattern, enabling motion capture without requiring multiple sequential patterns.
Solution Approach 2:
The patent transitions from traditional 1D or simple 2D patterns to complex 2D feature types with unique bi-dimensional formations. By encoding multiple distinguishable feature types within a single 2D pattern projection, the system achieves higher information density and enables dynamic object capture without increasing temporal complexity.
2Measurement precision
If traditional light patterns are projected, then the system is simpler to implement, but feature identification accuracy and precision deteriorate due to ambiguity
Solution Approach 1:
Different regions of the projected light pattern contain feature types with locally optimized characteristics (different shapes, sizes, orientations). Each feature type is designed with unique local properties that make it distinguishable from others, improving identification accuracy without requiring system-wide complexity increases.
Solution Approach 2:
The patent uses variations in feature type characteristics (analogous to color changes) where different feature types have distinct visual properties. This allows the imaging system to differentiate between multiple features in a single pattern projection, significantly improving measurement precision while maintaining manageable pattern complexity.
3Measurement precision
If features are allowed to appear multiple times on the same epipolar line, then the number of identifiable features increases, but ambiguity in feature identification increases and precision decreases
Solution Approach 1:
Multiple instances of feature types are distributed across different epipolar lines rather than repeating on the same line. Each feature type appears once per epipolar line, eliminating ambiguity. The system captures multiple features by having different feature types appear on the same epipolar line, maintaining precision while increasing the quantity of identifiable features.
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
This approach provides high-resolution, accurate 3D imaging capable of capturing moving objects by ensuring each feature type appears only once on a specific epipolar line, reducing ambiguity and increasing the number of identifiable features, thus enhancing the precision and reliability of 3D data acquisition.
Implementation Method 1
Through knowledge of the baseline distance, as well as projection and imaging angles, known geometric/triangulation equations are utilized to determine distance to the imaged object.
Implementation Method 2
capturing a 2D image of the objects having the projected coded light pattern projected thereupon, the 2D image comprising reflections of the feature types
Data Source
AI summary
A system, apparatus and method of obtaining data from a 2D image in order to determine the 3D shape of objects appearing in said 2D image, said 2D image having distinguishable epipolar lines, said method comprising: (a) providing a predefined set of types of features, giving rise to feature types, each feature type being distinguishable according to a unique bi-dimensional formation; (b) providing a coded light pattern comprising multiple appearances of said feature types; (c) projecting said coded light pattern on said objects such that the distance between epipolar lines associated with substantially identical features is less than the distance between corresponding locations of two neighboring features; (d) capturing a 2D image of said objects having said projected coded light pattern projected thereupon, said 2D image comprising reflected said feature types; and (e) extracting: (i) said reflected feature types according to the unique bi-dimensional formations; and (ii) locations of said reflected feature types on respective epipolar lines in said 2D image.