Stereo Camera Baseline Adjustment for Depth Precision
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
State-of-the-art stereo-camera systems face challenges in measuring object depth with optimal precision due to fixed camera distances and the need for excessive cameras and processing power, especially when objects are moving within the captured scene.
Innovation Solution
A method and system that adjust the imaging positions of cameras to optimize depth precision by determining a rough estimate of depth based on initial images, calculating improved imaging positions, and re-imaging to achieve higher precision, which involves moving cameras to positions along a straight line connecting the initial positions and selecting the optimal camera pair for improved depth measurement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the distance between multiple cameras is fixed in state of the art stereo-camera systems, then the system structure is simple, but the depth measurement precision cannot be optimized for moving objects
Solution Approach 1:
The patent applies the dynamics principle by making the camera baseline distance adjustable rather than fixed. The system dynamically changes the distance between cameras (or selects from multiple baseline configurations) to optimize depth measurement precision for objects at different depths, thereby adapting to moving objects in the scene.
Solution Approach 2:
The patent changes the physical parameter of baseline distance between cameras to optimize depth measurement. By adjusting this parameter based on object depth, the system achieves optimal measurement precision for moving objects at varying distances from the camera system.
2Measurement precision
If excessive cameras are used in state of the art stereo-camera systems, then depth measurement coverage is improved, but the device complexity and processing power requirements increase
Solution Approach 1:
The patent uses a dynamic approach where a small number of cameras (typically two) are used with adjustable baseline distances. By changing the baseline configuration rather than adding more cameras, the system achieves optimal depth measurement for different object distances without increasing device complexity.
Solution Approach 2:
Instead of increasing the number of cameras, the patent changes the baseline distance parameter to optimize depth measurement precision. This parameter-based optimization allows accurate depth measurement with minimal cameras, reducing device complexity and processing requirements.
3Measurement precision
If excessive processing power is used in state of the art stereo-camera systems, then depth measurement accuracy is improved, but energy consumption and system cost increase
Solution Approach 1:
The patent performs preliminary action by first obtaining a rough depth estimate using a simple method, then using this estimate to determine the optimal baseline distance for precise measurement. This two-stage approach avoids the need for excessive processing power in the initial phase while achieving high precision when needed.
Solution Approach 2:
The patent optimizes processing efficiency by changing the baseline parameter based on rough depth estimates. This allows the system to use minimal processing power for initial estimation and only apply precise measurement methods when necessary, reducing overall energy consumption while maintaining accuracy.
Data Source
AI summary
An exemplary technique is provided for obtaining an improved depth precision for a stereo image of an object of interest. The technique includes imaging a first image of the object of interest from a first position, imaging a second image of the object of interest from a second position different from the first position, determining a rough estimate of a depth for the object of interest based on the first image and the second image, determining an improved set of imaging positions corresponding to an improved depth precision for the object of interest based on the rough estimate of the depth, imaging improved images from the improved set of imaging positions, and determining an improved depth based on the improved images.