Dynamic Structured Light Pattern for Depth Sensing
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Solution Overview
Problem
Conventional structured light projectors in depth camera assemblies have fixed patterns that are not dynamically adjusted, leading to inefficient power consumption and inaccurate depth sensing due to either excessive or insufficient texture in different regions of the scene.
Innovation Solution
A depth camera assembly that generates a dynamic structured light pattern based on a virtual model of physical locations, adjusting texture and pattern density in real-time according to contrast values and other parameters received from a mapping server, allowing for optimized power usage and improved accuracy in depth measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a fixed structured light pattern is used, then the device complexity is reduced, but the measurement precision and power efficiency deteriorate due to inability to adapt to different scene conditions
Solution Approach 1:
The patent implements dynamic structured light patterns that can be adjusted in real-time based on scene conditions. The system modifies pattern density, contrast, and distribution dynamically to match the specific depth sensing requirements of different regions, thereby improving measurement precision without requiring overly complex fixed patterns.
Solution Approach 2:
The system changes key parameters of the structured light pattern including density, contrast, and spatial distribution based on scene analysis. By adjusting these parameters dynamically, the system optimizes depth sensing accuracy for different scene conditions while maintaining manageable device complexity.
2Measurement precision
If high pattern density is used throughout the scene, then measurement precision improves, but power consumption increases unnecessarily in regions where high resolution is not needed
Solution Approach 1:
The patent applies different pattern densities to different regions of the scene based on their specific requirements. High-density patterns are applied only to regions requiring high measurement precision, while low-density patterns are used in regions where lower resolution is acceptable, thereby optimizing power consumption while maintaining necessary measurement accuracy.
Solution Approach 2:
The system applies high pattern density only partially to specific regions of interest rather than uniformly across the entire scene. This selective application of high-density patterns to only where needed reduces overall power consumption while maintaining measurement precision in critical areas.
3Use of energy by moving object
If low pattern density is used, then power consumption decreases, but measurement precision deteriorates due to insufficient texture for accurate depth calculation
Solution Approach 1:
The system strategically places higher density patterns in specific local regions where depth measurement precision is critical, while using lower density patterns in other regions. This localized quality adjustment ensures adequate texture for accurate depth calculation in important areas while reducing power consumption in less critical areas.
Solution Approach 2:
The system dynamically adjusts pattern density parameters based on scene analysis and depth measurement requirements. By changing these parameters adaptively, the system ensures sufficient texture for accurate depth calculation where needed while minimizing power consumption where lower resolution is acceptable.
4Measurement precision
If uniform high contrast pattern is used, then measurement precision improves in low-contrast regions, but power consumption increases and pattern becomes too dense for distant or already high-contrast regions
Solution Approach 1:
The system adjusts pattern contrast locally based on the specific characteristics of different scene regions. High-contrast patterns are applied to low-contrast regions to improve measurement precision, while lower contrast patterns are used in already high-contrast regions, thereby optimizing power consumption while maintaining measurement accuracy where it matters most.
Data Source
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AI summary
A depth camera assembly (DCA) determines depth information. The DCA projects a dynamic structured light pattern into a local area and captures images including a portion of the dynamic structured light pattern. The DCA determines regions of interest in which it may be beneficial to increase or decrease an amount of texture added to the region of interest using the dynamic structured light pattern. For example, the DCA may identify the regions of interest based on contrast values calculated using a contrast algorithm, or based on the parameters received from a mapping server including a virtual model of the local area. The DCA may selectively increase or decrease an amount of texture added by the dynamic structured light pattern in portions of the local area. By selectively controlling portions of the dynamic structured light pattern, the DCA may decrease power consumption and/or increase the accuracy of depth sensing measurements.