Vehicle Image Projection Adjusted for Observer Position
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Solution Overview
Problem
Existing methods for projecting images onto a projection surface for motor vehicles only consider the driver's perspective, limiting the visibility and understanding of the image for observers outside the vehicle.
Innovation Solution
A method and device that adapt the projection of images based on the observer's position relative to the vehicle, integrating a light module to calculate and correct intensity values for a luminance map, ensuring the image is understandable by both inside and outside observers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the image projection is fixed for the driver's perspective, then the driver can understand the image, but external observers cannot understand the image
Solution Approach 1:
The projection system dynamically adjusts the image parameters (orientation, scale, position) based on the detected observer position. The processing unit calculates transformation matrices that map image coordinates to projection surface coordinates according to the observer's location, enabling the same projection device to adapt to different viewers without hardware changes
Solution Approach 2:
The system changes multiple image parameters simultaneously including rotation angle, scale factor, and projection position based on the observer's coordinates. These parameter transformations are computed in real-time to ensure the projected image remains understandable regardless of whether the observer is inside or outside the vehicle
2Adaptability or versatility
If the image is projected without considering observer position, then the projection device is simple, but the image is not understandable for external observers
Solution Approach 1:
The projection system automatically detects the observer's position and performs self-adjustment of image parameters without requiring manual configuration. The processing unit continuously monitors observer coordinates and autonomously computes the necessary transformations, making the system self-adapting while maintaining operational simplicity
Solution Approach 2:
The system uses feedback from observer position detection to continuously adjust projection parameters. The detected observer coordinates feed into the transformation calculation, creating a closed-loop system that automatically optimizes image comprehensibility for the current viewer position
3Loss of information
If the projection adapts to each observer's position, then all observers can understand the image, but the calculation and projection process becomes complex
Solution Approach 1:
The processing unit acts as an intermediary that translates between image coordinate system and projection surface coordinate system based on observer position. This intermediary layer handles the complex transformation calculations, isolating the complexity from both the light module and the final projection output
Solution Approach 2:
The patent replaces physical adjustment mechanisms with computational transformations. Instead of mechanically repositioning or reorienting projection components, the system uses software-based coordinate transformations to achieve the same effect, reducing mechanical complexity while maintaining adaptability
Data Source
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AI summary
The present invention relates to a projection method (MTH) for a motor vehicle (V) of at least one image (Ip) onto a projection surface (S) by means of a light module (ML) adapted to project a light beam (Fx), in which said projection method (MTH) comprises the steps of: - detecting an observation position (PosO1) of an observer (O) in a light module reference frame (RP); - calculating the observation position (PosO2) of the observer (O) in an image reference frame (RI); - projecting said image (Ip) onto said projection surface (S) as a function of said observation position (PosO2) of the observer (O) in said image reference frame (RI), said image (Ip) being integrated into said light beam (Fx) of the light module (ML).