360 Degree Surround View Stitching Using Radar-Stabilized 3D Bowl Model
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Solution Overview
Problem
Current automotive surround view systems face challenges in seamlessly stitching panoramic optical images around a vehicle, particularly due to ghost imaging issues caused by parallax in overlapping areas, which can be mitigated by integrating radar data to stabilize the 3D bowl surface model.
Innovation Solution
The method involves receiving optical images from multiple cameras, identifying seams between overlapping images, and using radar data to construct a 3D bowl surface model, linking optical images to radar data, and stitching them seamlessly based on direction and distance information to reduce ghost imaging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If optical images from multiple cameras are stitched together to create a 360-degree surround view, then a panoramic view is achieved, but ghost imaging issues occur in overlapping areas due to parallax
Solution Approach 1:
The patent introduces a 3D bowl surface model as an intermediary coordinate system to transform and stitch optical images from multiple cameras. This mediator enables seamless panoramic stitching by providing a common reference frame, while radar data serves as another intermediary to detect and correct ghost imaging artifacts in overlapping regions by identifying inconsistent object positions.
Solution Approach 2:
The system implements feedback by using radar data to detect ghost imaging issues in the stitched optical panorama and then correcting these artifacts. The radar-provided distance and position information feeds back into the stitching process to adjust and eliminate inconsistencies, improving overall image accuracy while maintaining full panoramic coverage.
2Reliability
If radar data is integrated to stabilize the 3D bowl surface model and reduce ghosting, then image accuracy improves, but system complexity increases
Solution Approach 1:
The patent applies multi-functionality by using radar data for multiple purposes: it stabilizes the 3D bowl surface model construction, provides distance information for accurate stitching, and simultaneously serves as a reference to detect and correct ghost imaging artifacts. This universal use of radar data improves image accuracy without requiring separate dedicated systems for each function.
Solution Approach 2:
The system merges optical camera data with radar data into a unified stitching and correction framework. By combining these different sensor types and their respective strengths (optical for detailed imagery, radar for accurate distance and position), the system achieves high image accuracy while consolidating multiple functions into an integrated process rather than separate systems.
Data Source
AI summary
A method of stitching panoramic optical images around a vehicle having, receiving a plurality of optical images from a plurality of image sensors mounted on the vehicle of a plurality of objects surrounding the vehicle, overlapping optical images of the plurality of objects surrounding the vehicle, identifying seams between the plurality of objects surrounding the vehicle within the plurality of optical images, receiving a plurality of radar images from a plurality of radar sensors mounted on the vehicle indicating at least one direction and at least one distance of at least one of the plurality objects surrounding the vehicle, linking the plurality of optical images of the plurality of objects surrounding the its vehicle to the plurality of radar images and stitching the plurality of optical images based on the plurality of radar images.