Automated Object Detection Validation via Reference Correlation
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Solution Overview
Problem
Existing methods for validating object detection equipment in vehicles are inefficient, requiring extensive human resources and time, and often necessitate complex calibration, which can be difficult and costly to maintain.
Innovation Solution
A method and system that automatically evaluate the accuracy of object detection equipment by correlating attributes of detected objects with those from validated reference equipment, using spatial and temporal attributes, and outputting differences for analysis, thereby reducing resource consumption and eliminating the need for rigid calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing methods for validating object detection equipment are used, then validation can be performed, but extensive human resources and time are required
Solution Approach 1:
The patent replaces manual validation processes with an automated computer-based system that performs object detection validation. The system automatically compares detection results from equipment under test with reference data, eliminating the need for extensive human analysis and significantly reducing validation time while maintaining accuracy assessment capabilities.
Solution Approach 2:
The validation system enables the object detection equipment to be self-evaluated by automatically comparing its detection outputs with reference equipment data. The computer system autonomously processes detection records, correlates objects between different equipment, identifies differences, and generates validation reports without requiring continuous human intervention.
2Measurement precision
If existing validation methods are used, then detection accuracy can be evaluated, but complex calibration is required which is difficult and costly to maintain
Solution Approach 1:
The patent extracts the calibration requirement from the validation process by using reference equipment data that already contains embedded spatial and temporal information. Instead of requiring separate calibration procedures, the system directly uses the reference equipment's detection records as the basis for comparison, eliminating complex calibration steps while maintaining accuracy evaluation.
Solution Approach 2:
The patent introduces a computer as an intermediary that manages the comparison between equipment under test and reference equipment. This intermediary system handles the complex tasks of correlating objects across different equipment, matching spatial and temporal attributes, and identifying differences, thereby simplifying the overall validation process without requiring direct calibration between physical equipment.
3Measurement precision
If manual validation processes are used, then comprehensive analysis can be performed, but extensive human resources are required
Solution Approach 1:
The patent replaces manual validation processes with an automated computer-based system that performs object detection validation. The system automatically compares detection results from equipment under test with reference data, eliminating the need for extensive human analysis and significantly reducing validation time while maintaining accuracy assessment capabilities.
Solution Approach 2:
The validation system enables continuous automated processing of detection records without interruption by human operators. The computer system can continuously correlate objects, compare attributes, and generate validation reports, maintaining productive validation action throughout the process without the breaks and limitations inherent in manual processes.
Data Source
AI summary
Presented herein are systems and methods for automatically evaluating detection accuracy of dynamic objects by equipment under test, comprising receiving a first record generated by an evaluated equipment under test and a second record generated by a validated reference equipment both deployed in a vehicle, the first record comprising a plurality of attributes of dynamic object(s) detected by the evaluated equipment and the second record comprising a plurality of attributes of dynamic object(s) detected by the reference equipment, correlating between dynamic object(s) detected by both the evaluated equipment and the reference equipment according to matching spatial and temporal attributes of the dynamic object(s) in the first record and in the second record, analyzing at least some of the attributes of the respective dynamic object in the first record compared to the second record, and outputting an indication of differences identified between the first record and the second record.


