Auto-aligning Image Sensors via Pixel Shift for 3D Depth Accuracy
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Solution Overview
Problem
Digital cameras with rolling shutters often capture images at different times due to misalignment, leading to rolling shutter artifacts and incorrect depth determinations in 3D images, especially when capturing moving scenes, as they struggle to synchronize image capture effectively.
Innovation Solution
A computer-implemented process synchronizes image sensors by identifying a pixel shift between captured images with an overlapping field of view, determining a time lag based on this shift, and calibrating the sensors to align subsequent image capture, allowing for time-synchronized image capture across multiple cameras.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cameras are aligned using a six-axis pan-tilt camera mount to synchronize image capture, then rolling shutter artifacts are reduced and image synchronization is improved, but the alignment process becomes time-consuming and operationally complex
Solution Approach 1:
The patent replaces the mechanical six-axis pan-tilt camera mount alignment system with an electronic/software-based solution. The system captures images from multiple cameras, identifies corresponding features, calculates pixel shifts, and determines time lags through computational processing. This substitution eliminates the need for complex mechanical alignment while achieving the same synchronization goal, thereby improving ease of operation without sacrificing reliability
Solution Approach 2:
The alignment system performs self-calibration by automatically capturing test images, identifying features, calculating pixel shifts, and determining time lags without requiring manual intervention. The system uses its own captured images to compute the necessary alignment parameters and applies corrections autonomously, making the alignment process self-service rather than operator-dependent
2Manufacturing precision
If manual alignment of image sensors is performed to synchronize capture timing, then rolling shutter artifacts are minimized, but the process requires significant time and expertise even for experienced photographers
Solution Approach 1:
The system performs automatic self-alignment by capturing images, identifying corresponding features between cameras, calculating pixel shifts, and determining time lags without human intervention. The alignment process is automated through computational algorithms that analyze the captured images and compute correction parameters, eliminating the need for time-consuming manual alignment while maintaining high precision
Solution Approach 2:
The system uses feedback from captured images to automatically adjust alignment parameters. By identifying features in images from multiple cameras and calculating the pixel shifts and time lags, the system creates a feedback loop that enables automatic correction of misalignment, replacing manual trial-and-adjustment processes with precise computational feedback
Data Source
AI summary
An image capture device having multiple image sensors having overlapping fields of view that aligns the image sensors based on images captured by image sensors. A pixel shift is identified between the images. Based on the identified pixel shift, a calibration is applied to one or more of the image sensors. To determine the pixel shift, a processor applies correlation methods including edge matching. Calibrating the image sensors may include adjusting a read window on an image sensor. The pixel shift can also be used to determine a time lag, which can be used to synchronize subsequent image captures.