Stereo Yaw Correction via Autofocus Feedback
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Solution Overview
Problem
Stereoscopic image sensors often experience misalignment due to factors like gravity, heat, and mechanical wear, leading to depth measurement errors and visual discomfort during 3D image viewing.
Innovation Solution
A system and method utilizing autofocus feedback to correct yaw misalignment in stereoscopic image sensors by capturing images, determining disparity, estimating stereoscopic depth, setting autofocus lens positions, and adjusting the yaw angle based on the difference between autofocus and stereoscopic depths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If stereoscopic image sensors are perfectly aligned during manufacturing, then initial image alignment quality is improved, but alignment drift occurs over time due to gravity, heat, and mechanical wear
Solution Approach 1:
The patent implements a feedback mechanism where the device continuously performs autofocus measurements and compares them with stereoscopic depth measurements. The system calculates yaw drift based on the discrepancy between these two measurement methods and automatically corrects the sensor alignment, creating a closed-loop control system that maintains alignment accuracy over time
Solution Approach 2:
The patent performs preliminary autofocus calibration to establish a reference relationship between autofocus lens position and stereoscopic depth before actual operation. This preliminary action creates a baseline that enables the system to detect and correct yaw drift during normal operation without requiring manual recalibration
2Measurement precision
If manual calibration procedures are implemented to correct sensor misalignment, then alignment accuracy is improved, but user operation complexity and time consumption increase
Solution Approach 1:
The patent enables the device to perform self-calibration by automatically detecting yaw drift through the comparison of autofocus and stereoscopic depth measurements, and then autonomously correcting the alignment. The system serves itself without requiring user intervention, specialized calibration targets, or manual adjustment procedures
Solution Approach 2:
The patent replaces manual mechanical calibration procedures with an automated computational system that uses software-based depth measurement comparison and automatic correction algorithms, eliminating the need for physical calibration objects and manual sensor adjustment
3Measurement precision
If complex calibration algorithms are used to correct yaw drift, then depth measurement precision is improved, but computational overhead and processing time increase
Solution Approach 1:
The patent focuses on correcting only the yaw component of sensor misalignment rather than performing full six-degree-of-freedom calibration. By concentrating on the specific yaw drift issue and using the existing relationship between autofocus and stereoscopic depth measurements, the system achieves effective correction with simplified processing
Solution Approach 2:
The patent leverages the autofocus system, which already exists in the device for focusing purposes, to also perform yaw drift detection and correction. This multi-functional use of the autofocus mechanism eliminates the need for separate calibration hardware or dedicated calibration algorithms, reducing overall system complexity
Data Source
AI summary
Systems and methods for correcting stereo yaw of a stereoscopic image sensor pair using autofocus feedback are disclosed. A stereo depth of an object in an image is estimated from the disparity of the object between the images captured by each sensor of the image sensor pair. An autofocus depth to the object is found from the autofocus lens position. If the difference between the stereo depth and the autofocus depth is non zero, one of the images is warped and the disparity is recalculated until the stereo depth and the autofocus depth to the object is substantially the same.