Stereo Camera Calibration Using Row Disparity Alignment
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Solution Overview
Problem
Stereo camera pairs in autonomous driving systems face challenges in accurate on-the-fly calibration due to relative movement between cameras, which is computationally intensive and inefficient.
Innovation Solution
A method that transforms images from a stereo camera pair to rectified images based on relative rotational or translational positions, selects specific pixel rows, compares them to determine disparity values, and adjusts the camera positions to optimize alignment, focusing on regions sensitive to long-range applications and distributing computation efficiently across frames.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional calibration methods are used to maintain accurate stereo camera alignment, then measurement precision is improved, but device complexity and computational resources increase
Solution Approach 1:
The patent segments the calibration process by selecting only specific rows of pixels from the image data rather than processing entire images. This segmentation of the data processing task reduces computational complexity while maintaining calibration accuracy by focusing computational resources on the most relevant portions of the image data that contain calibration information.
Solution Approach 2:
The patent extracts and processes only the necessary components for calibration by selecting specific rows of pixels that contain the most valuable calibration information. This extraction approach eliminates unnecessary computational overhead from processing redundant image data, thereby reducing device complexity while preserving measurement precision.
2Measurement precision
If full image processing is performed for calibration, then measurement precision is improved, but productivity decreases
Solution Approach 1:
The patent divides the image data into multiple rows and selectively processes only specific rows that contain critical calibration information. This segmentation enables faster processing by avoiding computation on entire images, thereby improving productivity while maintaining the precision needed for accurate calibration through targeted processing of essential data portions.
Solution Approach 2:
The patent applies partial action by processing only a subset of image data (specific rows) rather than performing complete image processing. This partial processing approach achieves sufficient calibration accuracy without the computational burden of full image analysis, thus improving processing speed and productivity while maintaining adequate measurement precision.
3Reliability
If on-the-fly calibration is performed frequently to account for camera movement, then reliability is improved, but use of energy increases
Solution Approach 1:
The patent segments the calibration computation by focusing on specific rows of pixels rather than processing complete images. This segmentation reduces the computational energy required for each calibration operation, enabling more frequent on-the-fly calibration to maintain reliability without excessive energy consumption.
Solution Approach 2:
The patent performs partial calibration processing by analyzing only essential image portions (selected rows) rather than complete images. This partial action approach provides sufficient calibration reliability for autonomous driving applications while significantly reducing the energy consumption associated with frequent calibration operations.
Data Source
AI summary
In some embodiments, a method includes receiving a first image and a second image from a stereo camera pair. The method includes selecting a first row of pixels from the rectified image and a set of rows of pixels from the second image and comparing the first row of pixels with each row of pixels from the set of rows of pixels to determine disparity values. The method includes determining a pair of rows of pixels having the first row of pixels and a second row of pixels from the set of rows of pixels. The pair of rows of pixels has an offset no greater than an offset between the first row of pixels and each row of pixels from remaining rows of pixels. The method includes adjusting, based on the offset, the relative rotational position between the first stereo camera and the second stereo camera.