Vehicle Camera Masking Instruction Using Spherical Coordinate Transformation
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Solution Overview
Problem
Fish-eye cameras on vehicles capture large portions of the vehicle body, which are not relevant for image-processing convenience and safety functions, leading to increased data processing volumes and potential misinterpretation of reflections on the vehicle body.
Innovation Solution
A method and device that use a predefined mask to exclude the vehicle body from image processing, generated using three-dimensional model data and optical properties of the camera, transforming interpolation points from a vehicle coordinate system to a spherical coordinate system to create a masking instruction for image information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If a wide-angle lens camera is used to capture a large field of view, then the coverage area is improved, but the volume of data to be processed increases
Solution Approach 1:
The patent extracts and removes the vehicle body area from the image processing workflow by creating a mask that identifies and excludes regions containing the vehicle body. This extraction principle directly reduces the data volume requiring processing while preserving the beneficial wide-field coverage, as only relevant areas outside the vehicle body are processed further.
Solution Approach 2:
The patent segments the image into different regions: vehicle body areas (masked out) and relevant external areas (processed). By dividing the image processing task into segmented regions with different treatment, the system maintains comprehensive field of view coverage while reducing processing load on irrelevant vehicle body portions.
2Area of stationary object
If the camera captures a large portion of the vehicle body, then the field of view is improved, but misinterpretation of reflections occurs
Solution Approach 1:
The patent extracts and removes vehicle body regions from the processed image output by applying a mask. This extraction eliminates the source of reflection misinterpretation while preserving the wide field of view capability, as reflected areas on the vehicle body are excluded from further processing and interpretation.
Solution Approach 2:
The patent converts the harmful effect of vehicle body reflections into a beneficial masking process. By identifying regions containing the vehicle body (where reflections occur) and systematically masking them, the system transforms the problem of unwanted reflections into a structured solution that improves interpretation reliability.
3Productivity
If a mask is created to exclude vehicle body areas, then data processing load is reduced, but the complexity of mask generation increases
Solution Approach 1:
The patent performs preliminary actions by pre-generating the mask using three-dimensional model data of the vehicle and camera parameters before actual image processing occurs. This preliminary mask creation, based on known geometric models rather than real-time image analysis, reduces processing complexity during operational use while maintaining high data processing efficiency.
Solution Approach 2:
The patent uses a three-dimensional model copy of the vehicle as the basis for mask generation instead of working directly with complex real-world image data. This modeling approach simplifies mask creation by using idealized geometric representations that can be mathematically transformed and applied to mask corresponding regions in actual images.
Data Source
AI summary
A method for producing a masking instruction for a camera of a vehicle, the method including a setting step, a transforming step, and a storing step. In the setting step, interpolation points of a field-of-view boundary are set in a vehicle coordinate system using three-dimensional model data of the vehicle, the interpolation points being set from a camera perspective that is modeled in the model data. In the transforming step, vehicle coordinates of the interpolation points from the vehicle coordinate system are transformed into a spherical coordinate system to obtain spherical coordinates of the interpolation points. In the storing step, a mask curve defined by the interpolation points, is stored in the spherical coordinate system in order to produce the masking instruction.