Face Data Registration Using Behavior Analysis
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Solution Overview
Problem
Existing customer information registration systems are inefficient due to the need for manual clerk determination, leading to bloated data capacity with low usefulness information, such as registering individuals seen briefly by cameras.
Innovation Solution
A system that includes a matching unit to compare face data from cameras against stored data, a behavior information acquisition unit to analyze customer behavior, and a condition determination unit to decide on data storage based on behavior, ensuring only relevant information is stored.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If customer information is registered based on manual clerk determination, then registration accuracy is improved, but operation efficiency deteriorates
Solution Approach 1:
The system automatically determines whether to register customer information by analyzing behavior information from multiple cameras, replacing manual clerk determination with self-service automation. The determination unit evaluates customer behavior patterns (such as browsing duration, product interaction, and store navigation) to autonomously decide on registration, eliminating the need for clerk intervention while maintaining registration accuracy.
Solution Approach 2:
The manual mechanical process of clerk determination is replaced with an automated information processing system that collects data from cameras, analyzes behavior patterns, and makes registration decisions algorithmically. This substitution of mechanical human judgment with automated computational analysis improves both efficiency and consistency.
2Quantity of substance
If all detected persons are registered as customers, then data completeness is improved, but data quality deteriorates
Solution Approach 1:
Instead of applying a uniform registration criterion to all detected persons, the system applies differentiated quality control by analyzing local behavior characteristics of each individual. The determination unit evaluates specific behavior patterns (such as browsing behavior, product examination, and store navigation patterns) to assess whether each person should be registered, ensuring that only those exhibiting customer-like behavior are included in the database.
Solution Approach 2:
The system changes the registration criterion from a simple binary detection parameter to a multi-dimensional behavior analysis parameter. By introducing behavior information parameters (duration of stay, areas visited, interaction with products), the system transforms the registration decision from a crude filter to a refined assessment, improving data quality without sacrificing completeness.
3Reliability
If registration requires clerk intervention, then registration reliability is improved, but device complexity increases
Solution Approach 1:
The camera system performs multiple functions: it not only captures customer images for identification but also analyzes behavior patterns for registration determination. By making the camera system multi-functional (serving both identification and behavior analysis purposes), the system reduces overall complexity while maintaining reliability, as the same hardware infrastructure supports multiple critical functions.
Solution Approach 2:
The determination unit acts as an intermediary that processes information from multiple sources (camera data, behavior analysis, existing customer database) and makes the final registration decision. This intermediary component coordinates the various system elements, ensuring reliable operation while managing system complexity through centralized intelligent control.
Data Source
AI summary
A matching unit configured to match face data of a customer based on image data acquired by a camera in a shop against face data stored in a storage unit, a behavior information acquisition unit configured to acquire behavior information according to a behavior of the customer in the shop, and a condition determination unit configured to determine whether or not to store the face data into the storage unit based on the behavior information acquired by the behavior information acquisition unit in a case where the matching fails are provided.