Image Recognition Accuracy Assessment via Identifier Comparison
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Solution Overview
Problem
Robots face challenges in determining the quality of image recognition and have limited resources for improving image recognition accuracy while in use, especially in environments where precise feature identification is necessary.
Innovation Solution
A system and method that utilize a robot equipped with an image capture device and local computing device to locate identifiers, determine actual and perceived object characteristics, and compare them to assess accuracy, allowing for adjustments to improve image recognition by modifying image recognition logic when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image recognition is performed by the robot in real-time during operation, then the robot can identify objects and navigate the environment, but the accuracy of image recognition cannot be easily determined or improved due to limited resources
Solution Approach 1:
The patent introduces an intermediary accuracy assessment system that includes identifier objects with known characteristics. These identifiers serve as mediators between the robot's image recognition system and the ground truth, enabling accuracy measurement without requiring complex external validation equipment. The identifier contains encoded actual characteristics that can be compared against perceived characteristics from image recognition.
Solution Approach 2:
The patent creates simplified copies of real-world objects in the form of identifier objects with predetermined formats and known characteristics. These identifier copies allow the robot to practice and be evaluated on image recognition in controlled scenarios, with the actual characteristics serving as reference copies for accuracy verification.
2Productivity
If the robot uses limited computational resources for image recognition tasks, then it can operate efficiently, but it lacks the resources to simultaneously perform comprehensive accuracy assessment and improvement
Solution Approach 1:
The patent implements preliminary action by pre-encoding actual characteristics into identifier objects before the robot encounters them. This allows the robot to focus computational resources on extracting perceived characteristics during operation, while the comparison with pre-stored actual characteristics can be performed efficiently without requiring extensive real-time computational resources for accuracy assessment.
Solution Approach 2:
The patent segments the image recognition system into distinct functional components: image capture, identifier detection, characteristic extraction, and accuracy comparison. This segmentation allows each component to operate with optimized resource allocation, where the identifier location module handles detection tasks separately from the accuracy assessment module, improving overall operational efficiency.
3Measurement precision
If the robot continuously improves image recognition logic based on accuracy assessment, then recognition accuracy increases, but the complexity of managing and updating recognition logic increases
Solution Approach 1:
The patent implements a feedback mechanism where the accuracy comparison between actual and perceived characteristics generates correction information that is fed back to update the image recognition logic. This closed-loop feedback system enables continuous improvement of recognition accuracy while maintaining systematic control over the adaptation process, preventing uncontrolled complexity growth.
Data Source
AI summary
Systems and methods for measuring image recognition accuracy are provided. One embodiment of a method includes locating an identifier in an environment, where the identifier is configured according to a predetermined format and where the identifier identifies an actual characteristic of an object. Some embodiments of the method include locating the object in the environment, determining a perceived characteristic of the object, and determining, from the identifier, the actual characteristic of the object. Similarly, some embodiments include comparing the actual characteristic of the object with the perceived characteristic of the object, determining whether the actual characteristic of the object substantially matches the perceived characteristic of the object and, in response to determining that the actual characteristic of the object does not substantially match the perceived characteristic of the object, determining a change to make for improving image recognition.