Stereo Depth Mapping Correction via Range Sensor Feedback
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Solution Overview
Problem
Existing stereoscopic depth mapping systems face challenges in accurately maintaining alignment between cameras due to environmental factors like vibrations and thermal fluctuations, leading to errors in depth mapping, particularly in detecting and correcting yaw errors.
Innovation Solution
The integration of a range-sensing module, such as a LiDAR sensor, with the stereoscopic depth mapping module allows for the measurement of ranges to points in the scene. A controller processes these measurements to compute a correction function, which is applied to subsequent depth maps to correct for alignment changes, including yaw errors, without requiring physical re-alignment of the cameras.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If stereoscopic depth mapping is used without correction, then the system structure remains simple, but alignment accuracy deteriorates due to environmental factors like vibrations and thermal fluctuations
Solution Approach 1:
The system computes a correction function by comparing ranges measured by the range-sensing module to depth coordinates in the depth map, then applies this correction function to subsequent depth maps. This feedback loop continuously corrects alignment errors caused by environmental factors without requiring physical re-alignment of cameras.
Solution Approach 2:
Instead of using mechanical adjustment mechanisms to physically realign cameras when alignment errors occur, the system substitutes a computational correction function that processes image data to correct depth mapping accuracy. This replaces complex mechanical adjustment systems with software-based correction.
2Measurement precision
If physical re-alignment of cameras is performed to correct alignment errors, then alignment accuracy improves, but the system requires manual intervention and stops operation
Solution Approach 1:
The system implements continuous feedback correction by computing correction functions from range data and applying them to subsequent depth maps in real-time. This eliminates the need to stop operation for manual re-alignment, maintaining both high accuracy and continuous productivity.
Solution Approach 2:
The system performs self-correction by automatically computing and applying correction functions to compensate for alignment errors. The stereoscopic depth mapping module corrects its own alignment issues without external intervention, maintaining continuous operation and high productivity.
3Measurement precision
If correction functions are computed and applied to subsequent depth maps, then alignment accuracy improves dynamically, but computational complexity increases
Solution Approach 1:
The system replaces complex mechanical alignment adjustment mechanisms with computational correction functions. While this introduces software processing, it eliminates the need for complex mechanical systems and manual intervention, achieving a different kind of simplicity through computation.
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 solution enables accurate and dynamic correction of camera alignment errors, particularly yaw errors, in real-world applications, improving the accuracy and reliability of depth mapping without the need for physical adjustments or known depth-mapping targets.
Implementation Method 1
measuring, by the range-sensing module, respective ranges to points in the scene
Data Source
AI summary
A depth mapping apparatus includes a stereoscopic depth mapping module, including a first and second cameras configured to capture pairs of respective first and second images of a scene, and a range-sensing module, configured to measure respective ranges from the apparatus to multiple points in the scene. A controller processes a first pair of the first and second images of the scene to compute a first depth map of the scene and associates at least some of the points at which the range-sensing module measured respective ranges with corresponding pixels in the first depth map. The controller computes a correction function for the stereoscopic depth mapping module by comparing the respective ranges measured by the range-sensing module to respective depth coordinates of the corresponding pixels in the first depth map and applies the correction function in computing subsequent depth maps based on subsequent pairs of the first and second images.