Virtual Window Scene Prediction for Inertial Camera Motion Compensation
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Solution Overview
Problem
Existing see-thru display systems, such as head-up displays, do not effectively provide a window-like view of the external environment when a clear view is desired, especially in situations where navigation and obstacle avoidance are necessary.
Innovation Solution
A virtual window system for vehicles that includes a display device and a controller, which receives images from an imaging system, predicts the vehicle's location at a future time, translates the image to account for position and angle changes, and displays the estimated view on the device, using factors like scenery angle change, scaling, and sliding factors to provide a realistic external view.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a see-thru display system is used to show external environment, then navigation and obstacle avoidance are improved, but the natural window-like view is blocked or compromised
Solution Approach 1:
The system creates a virtual copy of the external scene captured by imaging sensors and displays it on the see-thru display. This copy replaces the need for direct optical viewing while preserving the visual information, allowing the display to show navigation data without blocking the driver's natural view of the external environment
Solution Approach 2:
The system dynamically adjusts the transparency and visual properties of the see-thru display to optimize both the displayed information visibility and the underlying external scene visibility, creating a balanced overlay that provides navigation data while maintaining window-like viewing characteristics
2Measurement precision
If image translation and prediction algorithms are implemented, then the window-like view accuracy is improved, but the system complexity increases
Solution Approach 1:
The system pre-calculates translation parameters and predicts future vehicle positions based on current motion data. By performing these computations in advance and using predictive algorithms, the system achieves accurate real-time image adjustment without requiring complex real-time processing during critical moments
Solution Approach 2:
The system continuously monitors vehicle motion data from sensors and uses this feedback to dynamically adjust image translation and prediction parameters. This closed-loop approach maintains high accuracy while optimizing computational resources by adjusting processing intensity based on actual vehicle conditions
Data Source
AI summary
A virtual window system for a vehicle is disclosed. The virtual window system includes a display device and a controller. The controller is configured to: receive an image of a scene in a field of view (FOV) of an imaging system of the vehicle at an image capture time; predict a vehicle location at a predicted image display time; translate the image to a predicted image having an estimated view of the scene from the vehicle at the predicted vehicle location based on a predicted render time, a predicted display time, an amount of predicted position change between vehicle position at the image capture time and predicted vehicle position at the predicted image display time; and cause the translated image to be displayed on the display device at the predicted image display time.