Vehicle Camera Displacement Correction via Strain Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Vehicles equipped with stereo camera assemblies face errors in image data due to vibrations from road disturbances, leading to inaccuracies in three-dimensional image generation and object detection.
Innovation Solution
A system that collects strain data from cameras and operation data of vehicle components, using a machine learning program to determine camera displacement and apply transformation matrices to correct image data, thereby improving the accuracy of three-dimensional image generation and object detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If stereo camera assemblies are used to capture image data, then three-dimensional image generation capability is improved, but image data accuracy deteriorates due to vibrations from road disturbances
Solution Approach 1:
The patent introduces an intermediary processing system that receives image data from the stereo camera assembly and applies correction algorithms based on sensor data (accelerometers, gyroscopes, strain gauges). This intermediary processing layer mediates between the raw image data affected by vibrations and the final three-dimensional image output, compensating for vibration-induced errors without requiring physical isolation of the cameras.
Solution Approach 2:
The system implements feedback by continuously monitoring vibration parameters through sensors (accelerometers, gyroscopes, strain gauges) and using this information to dynamically adjust and correct image data processing. The correction algorithms use real-time vibration data to compensate for camera displacement and orientation changes, creating a closed-loop system that maintains image accuracy despite road disturbances.
2Measurement precision
If vibration compensation processing is applied to image data, then image data accuracy is improved, but processing time and computational complexity increase
Solution Approach 1:
The system performs preliminary action by pre-calculating and storing correction parameters and transformation matrices during periods when vibration data is available but image processing is not critical. The correction algorithms and transformation matrices are prepared in advance based on characterized vibration patterns, allowing faster application during actual image processing without real-time computational burden.
Solution Approach 2:
The patent applies partial correction by focusing computational resources on correcting only the most critical vibration-induced errors (camera displacement and orientation) rather than attempting to correct all possible image degradation factors. This selective correction approach maintains image accuracy while reducing overall processing complexity and time requirements.
Data Source
AI summary
A computer includes a processor and a memory storing instructions executable by the processor to input strain data measuring mechanical strain on a vehicle camera and operation data of a vehicle component, the operation data describing at least one of an output or a state of the vehicle component, to a machine learning program that outputs a displacement of the vehicle camera from a neutral position based on the strain data and the operation data. The instructions further include instructions to identify a transformation matrix that transforms data from the vehicle camera to a coordinate system of the vehicle camera in the neutral position based on the output displacement of the vehicle camera, to apply the transformation matrix to data collected by the vehicle camera to generate transformed data, and to actuate one of the vehicle component or a second vehicle component based on the transformed data.