Data Processing Apparatus Subject Extraction by Frequency
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Solution Overview
Problem
Existing data retrieval systems require pre-identification and specification of the subject to be retrieved, limiting their ability to find subjects satisfying predetermined conditions in various data types such as moving image, text, voice, music, and biometric data without prior feature value input.
Innovation Solution
A data processing apparatus and method that extracts subjects from data based on their appearance frequency, satisfying predetermined conditions, and outputs information about these subjects, allowing retrieval without prior subject identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a retrieval apparatus uses feature values of specified persons as retrieval keys, then retrieval accuracy is improved, but the system cannot retrieve subjects when the subject to be retrieved is not identified in advance
Solution Approach 1:
The system automatically extracts subjects and calculates their appearance frequencies without requiring user specification of retrieval targets. The apparatus serves itself by autonomously identifying what to retrieve based on frequency analysis, eliminating the need for pre-identified subjects while maintaining retrieval capability
Solution Approach 2:
The system changes the retrieval parameter from requiring pre-specified feature values to using automatically calculated appearance frequencies. By transforming the retrieval key from user-provided subject features to system-generated frequency metrics, the system achieves both accuracy and adaptability
2Measurement precision
If the system requires users to provide feature values for retrieval, then retrieval precision is improved, but the ease of operation deteriorates
Solution Approach 1:
The system automatically performs subject extraction and frequency calculation without requiring user input of feature values. This self-service mechanism maintains high retrieval precision while dramatically improving ease of operation by eliminating complex user interactions
Solution Approach 2:
The system performs preliminary subject extraction and frequency analysis automatically before retrieval operations. By pre-processing the data to identify subjects and calculate frequencies, the system prepares retrieval keys in advance without user involvement, ensuring both precision and ease of use
3Reliability
If the system analyzes all detected subjects to find those satisfying conditions, then retrieval completeness is improved, but processing time increases
Solution Approach 1:
The system extracts only the essential attribute (appearance frequency) needed for retrieval from the complex data. By focusing on this single key metric rather than analyzing all subject attributes, the system achieves complete retrieval of frequency-based subjects while minimizing processing time
Solution Approach 2:
The system creates a simplified copy of subject data containing only appearance frequency information for retrieval operations. This copied frequency data enables complete and accurate retrieval without processing the full complexity of original subject data, reducing time while maintaining completeness
Data Source
AI summary
A data processing apparatus (1) of the present invention includes a unit that retrieves a predetermined subject from moving image data. The data processing apparatus includes a person extraction unit (10) that analyzes moving image data to be analyzed and extracts a person whose appearance frequency in the moving image data to be analyzed satisfies a predetermined condition among persons detected in the moving image data to be analyzed, and an output unit (20) that outputs information regarding the extracted person.