Camera Object Detection Using Radar Calibration Ranges
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Solution Overview
Problem
Existing perimeter detection methods are prone to inaccuracies due to environmental factors such as weather and obstructions, leading to low accuracy in object detection results.
Innovation Solution
A method that combines radar detection signals with image analysis to improve object detection accuracy. The method determines spatial position information of an object using radar, and based on this information, calculates a calibration size range. It then compares this range with the actual size of the object in an image to determine if the object is a specified target.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If perimeter detection methods are used, then object detection can be performed, but accuracy deteriorates due to environmental factors and blocking articles
Solution Approach 1:
The patent combines radar detection signals with image analysis to achieve more accurate object detection. The radar module provides distance and speed information that is resistant to environmental interference, while the image module captures visual characteristics. By merging these two detection methods, the system overcomes the limitations of single-mode detection and improves overall accuracy despite environmental factors.
Solution Approach 2:
The patent introduces a calibration size range as an intermediary parameter that bridges radar detection and image analysis. This calibration range, derived from radar distance information, serves as a reference to verify object identification from images, thereby mediating between the two detection modalities and improving robustness against environmental interference.
2Reliability
If radar detection is used, then resistance to environmental interference is improved, but device complexity increases
Solution Approach 1:
The patent integrates radar and image detection systems into a unified detection apparatus. The radar module and image module work together with a processor that coordinates their operations, merging the advantages of both systems while managing the increased complexity through integrated processing.
Solution Approach 2:
The detection system is designed with multi-functionality, where the radar module provides both distance measurement and speed detection, and the image module serves both visual identification and size verification. This universal design allows a single integrated system to perform multiple detection functions, improving reliability while managing complexity through functional consolidation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the accuracy of object detection by leveraging the radar's resistance to environmental interference, allowing for more precise determination of object size and position, thereby improving overall detection reliability.
Implementation Method 1
based on a radar detection signal for detecting a to-be-detected object, determining spatial position information of the to-be-detected object
Data Source
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AI summary
An object detection method and a camera device. The method includes: based on a radar detection signal for detecting a to-be-detected object, determining spatial position information of the to-be-detected object, where the spatial position information at least includes: distance information of the to-be-detected object relative to the camera device and speed information of the to-be-detected object (101); in response to that the speed information satisfies a preset speed requirement, based on the distance information, determining a calibration size range corresponding to the to-be-detected object, and based on a collected image containing the to-be-detected object, determining an actual size of the to-be-detected object, where the calibration size range is used to represent, when the to-be-detected object is a specified object, a size range of the specified objected in the image (102); based on the actual size and the calibration size range, determining whether the to-be-detected object is the specified object (103).