Vehicle Camera Viewpoint Normalization for Virtual Image Views
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Solution Overview
Problem
The mass production of various vehicle models faces challenges due to differences in viewing angles and camera geometries, which can result in viewpoint differences and complicate processing systems, especially for fisheye cameras.
Innovation Solution
A system that captures image data from vehicle cameras, converts first viewpoint parameters into virtual viewpoint parameters using stored conversion information, and generates a virtual image view, allowing for consistent processing across different camera types and installations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If different camera types and installation configurations are used for mass production of vehicle models, then manufacturing flexibility and adaptability are improved, but viewpoint parameter consistency and processing system complexity deteriorate
Solution Approach 1:
The patent introduces a viewpoint parameter conversion module as an intermediary between the diverse camera configurations and the processing system. This module receives image data from various camera types (fisheye, pinhole, cylindrical) with different installation parameters, converts their viewpoint parameters to a standardized virtual viewpoint, and outputs normalized image data. This intermediary layer shields the processing system from the complexity of multiple camera configurations while maintaining manufacturing flexibility.
Solution Approach 2:
The patent applies parameter transformation by converting viewpoint parameters (installation position, angle, camera type) from their original diverse states to a standardized virtual viewpoint state. The conversion module uses stored conversion information specific to each camera configuration to transform the parameters, enabling consistent processing despite hardware variations. This parameter standardization resolves the contradiction between adaptability and processing complexity.
2Manufacturing precision
If viewpoint parameter conversion is implemented for each camera type, then image data normalization is improved, but data processing time and computational resources increase
Solution Approach 1:
The patent implements preliminary action by pre-storing conversion information for various camera types and configurations in a database. During runtime, the conversion module simply retrieves the appropriate conversion parameters based on camera identification rather than performing complex real-time calculations. This pre-computation approach maintains high normalization precision while significantly reducing processing time and computational resource requirements.
Solution Approach 2:
The patent uses copying by creating virtual copies of standardized viewpoint parameters for different camera configurations. Instead of processing each unique camera type individually, the system stores conversion information that maps various camera configurations to a standard virtual viewpoint. This copying approach enables rapid parameter transformation while ensuring consistent normalization across all camera types.
3Ease of operation
If a single processing application is used across multiple vehicle models, then system simplicity and ease of operation are improved, but performance degradation occurs when camera viewpoints deviate from assumptions
Solution Approach 1:
The patent implements universality by designing a single processing application that can handle multiple camera types and configurations through the viewpoint parameter conversion module. The conversion module acts as an adapter that standardizes input from various camera configurations, allowing one processing application to universally process image data from different vehicle models without modification. This maintains ease of operation while preserving processing performance.
Solution Approach 2:
The viewpoint parameter conversion module serves as an intermediary that bridges the gap between diverse camera viewpoints and the assumptions of the processing application. By converting all incoming image data to a standardized virtual viewpoint that matches the application's expected input parameters, the intermediary ensures the application operates reliably across all vehicle models without performance degradation.
Data Source
AI summary
A system for producing a virtual image view for a vehicle is provided. The system includes one or more image capture means configured to capture image data in proximity to the vehicle, the image data being defined at least in part by first viewpoint parameters, and to provide an identifier identifying the respective one or more image capture means, storage means configured to store a plurality of virtualization records containing conversion information related to a virtualized viewpoint and a plurality of image capture means, and processing means. The processing means are configured to receive the captured image data, convert the first viewpoint parameters of the captured image data into virtual viewpoint parameters based on the conversion information associated with a virtualization record stored by the storage means, to result in the virtual image view, wherein the virtualization record is identified at least based on the identifier, and execute at least one driver assistance and/or automated driving function based on the virtual image view.