Camera Radar Fusion via Coordinate Transformation
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Solution Overview
Problem
The fusion of camera and radar data in autonomous vehicles is challenging due to differences in sensor parameters, leading to inaccurate object detection and location, as radar and camera sensors provide data with different resolutions and coordinate systems, making it difficult to determine the same object's dimensions and location consistently.
Innovation Solution
A system that transforms vertical image plane camera images to horizontal image planes, generates scaled radar images based on camera image resolution, and superimposes these images to align object locations, allowing for accurate fusion of data and improved object detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If camera and radar data are fused directly without transformation, then the processing is simple and fast, but the object detection accuracy deteriorates due to different sensor parameters and coordinate systems
Solution Approach 1:
The patent introduces an intermediary coordinate transformation process that converts radar data into the camera's coordinate system. This mediator layer resolves the incompatibility between different sensor parameter systems, allowing accurate object detection by enabling direct comparison and fusion of camera and radar data in a unified coordinate framework
Solution Approach 2:
The patent applies parameter transformation by changing the coordinate system parameters of radar data to match camera parameters. This includes transforming spatial coordinates, scaling dimensions, and adjusting resolution parameters so that radar objects can be accurately located and sized within the camera image coordinate system
2Measurement precision
If coordinate transformation and scaling is applied to match sensor resolutions, then object location accuracy improves, but processing time and computational load increase
Solution Approach 1:
The patent performs preliminary coordinate transformation and scaling operations on radar data before the actual object detection and fusion process. By pre-aligning the radar coordinate system with the camera coordinate system and pre-scaling to match resolutions, the system eliminates the need for complex real-time transformations during detection, thereby reducing processing time while maintaining high location accuracy
Data Source
AI summary
A system includes a computer that includes a processor and a memory. The memory stores instructions executable by the processor such that the computer is programmed to transform a vertical image plane camera image to a horizontal image plane, thereby generating a transformed camera image, generate a scaled horizontal image plane radar image based on a resolution of the transformed camera image, and then superimpose the scaled radar image on the transformed camera image thereby generating a horizontal image plane superimposed image.