Tiered Camera Array for VR Light-Field Capture
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Solution Overview
Problem
Current volumetric capture systems for virtual reality struggle with sparse sampling of light-field volumes, leading to gaps in coverage and limitations in delivering high-quality playback with six degrees of freedom, due to challenges in estimating object properties like 3D geometry and reflectance with sufficient accuracy.
Innovation Solution
Implementing a tiered camera array with varying resolution and density, along with confidence mapping to prioritize high-resolution cameras for accurate world property estimation and interpolation, and using lower resolution cameras for regions with low confidence, thereby enhancing the quality of virtual reality experiences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a relatively large number of cameras are used to sparsely sample the light-field volume, then coverage gaps are reduced, but system complexity and costs increase
Solution Approach 1:
The camera array is segmented into multiple tiers with different resolutions and densities. High-resolution cameras are strategically placed in regions requiring accurate world property estimation, while lower-resolution cameras cover regions with lower confidence requirements. This segmentation allows the system to achieve comprehensive coverage without uniformly deploying high-density high-resolution cameras throughout the entire volume, thus reducing overall system complexity while maintaining reliability.
Solution Approach 2:
Different regions of the light-field volume are assigned different quality levels based on their importance for world property estimation. Regions with high confidence requirements (e.g., areas containing fine objects like hair) are captured by high-resolution cameras, while other regions use lower-resolution cameras. This local quality differentiation optimizes the balance between coverage completeness and system complexity by allocating resources where they are most needed.
2Measurement precision
If camera density is increased to reduce interpolation requirements, then interpolation accuracy improves, but system requirements and costs increase
Solution Approach 1:
The system dynamically changes the parameter of camera resolution based on the confidence level of world property estimation in different regions. Instead of using uniform high-resolution cameras throughout, the system employs variable resolution cameras matched to the local confidence requirements. This parameter change allows the system to achieve necessary interpolation accuracy while significantly reducing the total quantity and system requirements of high-resolution cameras needed.
Solution Approach 2:
The system applies high-resolution capture only partially, specifically in regions where world property estimation confidence is low and interpolation accuracy is critical. In regions with high confidence, lower-resolution cameras suffice. This partial application of high-resolution capture avoids the excessive use of high-density high-resolution cameras throughout the entire volume, reducing system requirements while maintaining necessary interpolation accuracy where it matters most.
3Measurement precision
If high-resolution cameras are used throughout the array, then world property estimation accuracy improves, but processing and storage requirements increase
Solution Approach 1:
The system applies high-resolution data capture and processing only locally in regions where world property estimation accuracy is critical (low confidence regions). In other regions with sufficient confidence, lower-resolution data is used. This local quality approach ensures that processing energy is expended only where necessary to achieve accurate world property estimation, rather than uniformly across the entire light-field volume, thus reducing overall processing energy consumption while maintaining estimation accuracy where needed.
Data Source
AI summary
A light-field camera system such as a tiled camera array may be used to capture a light-field of an environment. The tiled camera array may be a tiered camera array with a first plurality of cameras and a second plurality of cameras that are arranged more densely, but have lower resolution, than those of the first plurality of cameras. The first plurality of cameras may be interspersed among the second plurality of cameras. The first and second pluralities may cooperate to capture the light-field. According to one method, a subview may be captured by each camera of the first and second pluralities. Estimated world properties of the environment may be computed for each subview. A confidence map may be generated to indicate a level of confidence in the estimated world properties for each subview. The confidence maps and subviews may be used to generate a virtual view of the environment.