Light Field Camera Baseline and Convergence Tuning for 3D Depth
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Solution Overview
Problem
Existing multiview image capture systems lack the ability to dynamically adjust baseline and convergence distance based on the 3D content, leading to suboptimal depth perception and realism in 3D displays.
Innovation Solution
A method and system for determining and adjusting the baseline and convergence distance of a multiple camera rig based on 3D scene depths, using techniques such as ray casting, disparity maps, and depth sensors to dynamically set these parameters, allowing for real-time adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If baseline and convergence distance are fixed in multiview image capture systems, then device complexity is reduced, but depth perception and realism deteriorate
Solution Approach 1:
The patent implements dynamic adjustment of baseline and convergence distance parameters based on the 3D content being captured. The system automatically modifies these parameters in real-time according to the depth distribution and characteristics of the scene, enabling adaptive optimization of depth perception without requiring manual intervention or complex hardware reconfiguration.
Solution Approach 2:
The system changes the baseline distance between cameras and convergence distance parameters dynamically based on scene analysis. By adjusting these critical parameters according to the 3D content characteristics, the system optimizes multiview image quality and depth perception while maintaining a relatively simple camera rig structure.
2Adaptability or versatility
If baseline and convergence distance are adjusted manually, then device complexity is reduced, but adaptability to changing 3D content deteriorates
Solution Approach 1:
The system incorporates automatic feedback mechanisms that analyze the 3D content being captured and use this information to dynamically adjust baseline and convergence distance parameters. The feedback loop continuously monitors scene depth characteristics and automatically modifies camera parameters to optimize multiview image quality, eliminating the need for manual adjustment while enhancing adaptability.
Solution Approach 2:
The system performs self-adjustment of baseline and convergence distance parameters based on automatic analysis of the 3D scene. The camera rig autonomously determines optimal parameter settings without external intervention, enabling real-time adaptation to changing content while maintaining operational simplicity for the user.
3Reliability
If multiple cameras are used to capture multiview images, then depth perception is improved, but device complexity and cost increase
Solution Approach 1:
The patent employs a dynamic parameter adjustment strategy that optimizes the performance of the camera rig by continuously modifying baseline and convergence distance settings based on scene characteristics. This approach maximizes the depth perception capability of the existing camera configuration without requiring additional cameras or hardware additions.
Solution Approach 2:
The system achieves enhanced depth perception by intelligently adjusting operational parameters (baseline and convergence distance) rather than increasing hardware complexity. By optimizing these parameters dynamically, the system extracts maximum performance from the existing camera rig without adding more cameras or increasing device complexity.
Data Source
AI summary
A light field camera system and method of setting a baseline and a convergence distance of a multiple camera rig employ sample point depths to determine and set values with respect to a three-dimensional (3D) scene. A baseline and a convergence distance of a multiple camera rig is set by determining a plurality of sample point depths representing distances between the multiple camera rig and a plurality of sample points in the 3D scene within a field of view of the multiple camera rig. The convergence distance is set to be an average sample point depth of the plurality of sample point depths. The baseline is then set as a negative inverse of a difference between a minimum sample point depth of the plurality of sample point depths and the convergence distance. The light field camera system includes a multiple camera rig comprising a plurality of cameras.