Worker Operation Time-Series Analysis for Temporal Difference Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing techniques fail to efficiently indicate the relationship between the work operations of beginners and skilled workers through image analysis, particularly for those with little experience, necessitating a more effective method to identify temporal differences in their operations.
Innovation Solution
An information processing apparatus and method that analyzes time-series data of worker operations using dynamic time warping to associate and detect temporal differences between proficient and beginner workers, providing feedback on operation delays and improvements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If work analysis is performed using captured data from cameras and skeleton position information, then the ability to analyze worker operations is improved, but the efficiency of indicating temporal differences between beginner and skilled worker operations deteriorates
Solution Approach 1:
The patent segments the work operations into discrete time-series frames and associates them using dynamic time warping. This allows precise temporal difference detection by breaking down continuous operations into comparable discrete units, resolving the contradiction between analysis precision and efficiency.
Solution Approach 2:
The system provides feedback by visually indicating temporal differences between beginner and skilled worker operations through frame association. This feedback mechanism efficiently communicates analysis results without requiring complex interpretations, improving both precision and efficiency simultaneously.
2Productivity
If detailed work operation analysis is provided to beginners, then skill development effectiveness is improved, but the complexity of the analysis system increases
Solution Approach 1:
The patent uses frame association as an intermediary mechanism between raw operation data and skill development feedback. By associating time-series frames between beginner and skilled operations, the system provides detailed skill development information without requiring complex analysis algorithms, thus improving productivity while controlling complexity.
3Measurement precision
If temporal differences between operations are detected through frame association, then the precision of identifying operation delays is improved, but the computational time required increases
Solution Approach 1:
The patent applies dynamic time warping to associate time-series frames flexibly, allowing temporal differences to be detected with high precision. The dynamic association method adapts to varying operation speeds while maintaining computational efficiency, resolving the contradiction between detection precision and computational time.
Data Source
AI summary
An information processing apparatus according to an embodiment is capable of detecting whether or not there is a temporal difference between a first operation and a second operation different from the first operation based on presence or absence of a frame included in only either first time-series data related to the first operation and second time-series data related to the second operation, the first time-series data and the second time-series data being associated in units of time-series frames.