Appearance Detection Threshold Apparatus for Suspicious Person Identification
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Solution Overview
Problem
Current methods for detecting suspicious persons in images are limited by the reliance on a single feature, such as flow line abnormality, which restricts detection accuracy.
Innovation Solution
A processing apparatus and method that extracts multiple types of feature values from images, including face, body shape, gait, and belongings, and determines changes in appearance by comparing these features against stored data, using threshold values and weighting coefficients to identify suspicious individuals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple types of feature values are extracted and compared, then detection accuracy of suspicious persons improves, but device complexity and processing time increase
Solution Approach 1:
The patent segments the suspicious person detection task into multiple independent feature extraction modules, each handling a specific type of feature (face, body shape, gait, belongings). This segmentation allows the system to process different features separately and combine results, improving detection accuracy while managing system complexity through modular design.
Solution Approach 2:
The patent implements a universal detection framework that handles multiple types of features (face, body shape, gait, belongings) using a common processing architecture. The system extracts, manages, and compares different feature types through unified modules, enabling multi-functional detection capabilities without requiring entirely separate systems for each feature type.
2Measurement precision
If multiple types of feature values are extracted and compared, then detection accuracy of suspicious persons improves, but processing time increases
Solution Approach 1:
The patent extracts and manages multiple types of feature values (face, body shape, gait, belongings) in advance before the actual detection and comparison process. By preparing feature data beforehand and organizing it in a structured manner, the system reduces the computational burden during real-time detection, thereby improving detection accuracy while minimizing processing time delays.
3Reliability
If feature values are stored and compared against threshold values, then ability to detect disguised or suspicious persons improves, but data storage requirements and processing complexity increase
Solution Approach 1:
The patent extracts and stores only the essential feature values (face, body shape, gait, belongings) that are critical for suspicious person detection, rather than storing complete image data or all possible attributes. This selective extraction reduces data storage requirements while maintaining detection reliability by focusing on the most discriminative features for identifying suspicious behavior and appearance changes.
Data Source
AI summary
The present invention provides a processing apparatus including: an image analysis unit configured to extract a plurality of types of feature values of a person detected from an image; a registration management unit configured to determine whether or not data of the detected person is stored in a storage unit in which the feature value of each of a plurality of persons is stored on the basis of the extracted feature value; a change determination unit configured to determine whether or not there is a change in appearance of the detected person on the basis of the feature value stored in the storage unit and the extracted feature value in a case where it is determined that the data of the detected person is stored; and a notification unit configured to give notice of a person determined to have a change in appearance.