Sensor Data Annotation Verification Using Error-Priority Routing
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Solution Overview
Problem
Verifying annotations of sensor data in self-driving vehicles to identify features or characteristics of objects is difficult and complicated.
Innovation Solution
A signal processing system that routes sensor data annotations to a particular destination based on the error and priority level of the annotation by comparing them with annotation criteria, enabling a fully or partially automated verification process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual verification of sensor data annotations is performed, then accuracy can be maintained, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The patent introduces an automated verification system that acts as an intermediary between annotation creation and final usage. This system uses sensor data processing and comparison algorithms to automatically verify annotations, reducing reliance on manual verification while maintaining accuracy through multiple verification stages and confidence thresholding.
Solution Approach 2:
The patent replaces the mechanical process of manual annotation verification with an automated computational system. The system uses sensor data processing, algorithmic comparison, and automated decision-making to verify annotations, eliminating the need for human reviewers while improving verification speed and consistency.
2Reliability
If comprehensive annotation verification is performed, then annotation quality improves, but system complexity increases
Solution Approach 1:
The patent divides the annotation verification process into multiple independent stages: initial automated verification, confidence threshold checking, selective manual review, and final validation. Each stage handles specific aspects of verification, reducing overall system complexity while maintaining comprehensive quality control through modular processing.
Solution Approach 2:
The patent applies different verification rigor levels to different annotation types or confidence levels. High-confidence annotations receive streamlined verification, while low-confidence or critical annotations undergo more thorough checking. This localized approach to verification quality reduces unnecessary complexity in the overall system.
3Productivity
If automated verification systems are implemented, then verification speed increases, but initial development costs increase
Solution Approach 1:
The patent implements preliminary automated filtering and verification steps that process the majority of annotations automatically before they reach manual review. This preliminary action reduces the burden on expensive manual verification resources while maintaining high overall verification speed through a hybrid automated-manual approach.
Solution Approach 2:
The patent applies automated verification at varying levels of thoroughness depending on annotation confidence and criticality. Not all annotations receive the same level of automated verification intensity, optimizing the balance between verification speed and resource allocation while maintaining adequate quality control.
Data Source
AI summary
Provided are methods for automated verification of annotated sensor data, which can include receiving annotated image data associated with an image, wherein the annotated image data comprises an annotation associated with an object within the image, determining an error with the annotation based at least in part on a comparison of the annotation with annotation criteria data associated with criteria for at least one annotation, determining a priority level of the error, and routing the annotation to a destination based at least in part on the priority level of the error. Systems and computer program products are also provided.