Surround View Camera Distortion Correction Using Historical Obstacle Images
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Solution Overview
Problem
Surround view camera systems in vehicles often distort obstacles' appearance, leading operators to misjudge their position and size, which can result in navigation errors.
Innovation Solution
A method and system that utilize multiple imaging devices and a processor to generate composite surround view images by replacing distorted object data with non-distorted data from historical images, reducing the Manhattan effect and providing an accurate representation of obstacles' size and position.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If multiple imaging devices are combined to generate a surround view, then the operator can view the surroundings of the vehicle, but obstacles appear distorted and their actual size and position cannot be accurately judged
Solution Approach 1:
The system creates a virtual copy of the obstacle by generating a virtual image from historical camera data when the obstacle is detected in a distorted state. This virtual copy represents the obstacle's true dimensions and position, which then replaces or corrects the distorted visual information in the composite surround view image.
Solution Approach 2:
The system changes the parameters of the obstacle representation by calculating its true size and position parameters from historical undistorted images, then using these corrected parameters to generate an accurate virtual image that replaces the distorted visual data.
2Speed
If real-time images are used to show current surroundings, then the operator gets up-to-date information, but the images contain distortion when the vehicle is moving
Solution Approach 1:
The system performs preliminary actions by capturing and storing historical images of obstacles when they are first detected in undistorted states. These pre-captured images serve as reference data that can be later used to generate accurate virtual representations when real-time images become distorted.
Solution Approach 2:
The system creates a virtual copy of the obstacle using historical data, allowing the display to show both the current real-time surround view and the accurate virtual representation of obstacles, thereby maintaining information freshness while correcting distortion.
3Reliability
If the surround view is generated using current camera data, then the view reflects the current position of the vehicle, but obstacles appear with distorted appearance
Solution Approach 1:
The system generates a virtual copy of the obstacle with correct shape and size parameters from historical data, then superimposes or replaces this accurate copy over the distorted obstacle appearance in the real-time composite surround view image.
Solution Approach 2:
The system changes the shape parameters of the obstacle representation by calculating true dimensions from historical undistorted images and applying these corrected parameters to generate an accurate virtual image that maintains current position context while fixing appearance distortion.
Data Source
AI summary
A method of operating a surround view camera system for a vehicle includes generating first image data at a first time using a first imaging device operably connected to the vehicle, and generating second image data at a second time using a second imaging device operably connected to the vehicle. The second time is different from the first time, and the second imaging device different from the first imaging device. The method also includes identifying distorted object data in the second image data using a processor configured to receive the first image data and the second image data. The distorted object data corresponds to a predetermined object in a surroundings of the vehicle. The method includes identifying non-distorted object data in the first image data using the processor. The non-distorted object data corresponds to the predetermined object.