3D ML Model for Vehicle View Generation
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Solution Overview
Problem
Conventional infotainment systems in vehicles are limited by storage capacity, allowing only a finite number of two-dimensional images of vehicle views to be stored, restricting user access to desired views of the vehicle or its components.
Innovation Solution
An electronic system utilizing a trained three-dimensional machine learning model, generated from a set of two-dimensional images, allows for the generation and display of various views of the vehicle or its components on demand, eliminating the need to store all possible images and optimizing storage usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple two-dimensional images of vehicle views are stored in memory, then users can access various views of the vehicle, but the storage capacity is limited and cannot accommodate all possible views
Solution Approach 1:
The patent creates a three-dimensional model as a digital copy of the vehicle based on a set of two-dimensional images. This 3D model serves as a virtual replica that can generate any desired view without requiring physical storage of all possible 2D images. The 3D model is stored in memory instead of multiple 2D images, significantly reducing storage requirements while providing unlimited view accessibility.
2Loss of information
If all possible views of the vehicle are stored as images, then complete visual information is available, but the storage size becomes excessively large
Solution Approach 1:
The patent transitions from storing two-dimensional images to creating a three-dimensional model. By moving to a higher dimension (3D space), the system can represent the entire vehicle structure and appearance in a compact form. This 3D model can then generate any 2D view by projecting from the 3D space, preserving complete visual information while occupying minimal storage space compared to storing every possible 2D image.
3Quantity of substance
If a limited number of vehicle views are stored, then storage requirements are met, but users cannot access desired views that are not stored
Solution Approach 1:
The three-dimensional model serves multiple functions: it can generate any view of the vehicle from any angle, provide detailed component views, and accommodate user requests for specific perspectives. This single 3D model replaces the need for multiple specific 2D images, making the system universal in its ability to provide any desired view while maintaining low storage requirements.
Data Source
AI summary
An electronic system for a vehicle includes a memory and a control circuitry. The memory stores a three-dimensional (3D) model associated with the vehicle. The 3D model is a trained machine learning (ML) model that is trained using a first set of two-dimensional (2D) images as training data associated with the vehicle. The control circuitry receives a user input to display user-assistive information associated with the vehicle. The control circuitry generates a visual representation that corresponds to at least one of a first view of the vehicle or a second view of a component of the vehicle, based on the stored 3D model. The generated visual representation is different from the first set of 2D images. The control circuitry controls display of the user-assistive information that includes the generated visual representation on a display screen of the vehicle.