Computer Vision Demographic Measurement for Retail Spaces
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Solution Overview
Problem
Existing methods for customizing media content and measuring media advertising effectiveness in physical spaces, such as retail stores, rely on cumbersome manual input or non-automatic demographic data collection, lacking the ability to automatically characterize physical spaces based on actual demographic composition using computer vision technologies.
Innovation Solution
A method and system utilizing computer vision technologies for automatic demographics measurement, including face detection, person tracking, and demographic classification, to characterize physical spaces by analyzing captured visual information, enabling efficient and robust characterization of retail spaces without manual customer input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual demographic data collection methods are used, then data can be obtained, but the process is cumbersome and requires significant customer input
Solution Approach 1:
The patent replaces manual demographic data collection systems with an automated computer vision system using image capture devices and algorithms. The system automatically detects, tracks, and classifies demographic characteristics of customers in retail spaces without requiring any manual customer input or interaction, thus substituting mechanical/manual processes with automated optical and computational systems.
Solution Approach 2:
The system enables self-service demographic measurement by automatically capturing and analyzing customer images without requiring customers to provide any information. The computer vision algorithms independently perform detection, tracking, and classification tasks, allowing the system to serve itself in collecting demographic data without human intervention from the customers being measured.
2Extent of automation
If computer vision technologies are implemented for automatic demographics measurement, then automation is improved, but system complexity increases
Solution Approach 1:
The patent segments the complex demographic measurement task into distinct functional modules: image capture devices for data collection, detection algorithms for identifying demographic characteristics, tracking algorithms for following customer movements, and classification algorithms for categorizing demographics. This segmentation allows each component to be optimized independently and simplifies the overall system architecture despite the high level of automation achieved.
Solution Approach 2:
The system employs universal computer vision algorithms and image processing techniques that can handle multiple demographic measurement tasks simultaneously. The same core image capture and processing infrastructure supports detection, tracking, and classification functions, reducing the need for separate specialized systems for each function and thereby managing complexity while maintaining high automation.
3Measurement precision
If detailed demographic classification is performed, then measurement precision is improved, but processing time increases
Solution Approach 1:
The patent applies partial classification action by focusing computer vision analysis on key demographic characteristics that are most relevant for retail applications, rather than attempting to classify every possible attribute. The system performs detection and classification on prioritized demographic features, achieving sufficient measurement precision for marketing purposes without the excessive processing time that would result from comprehensive detailed classification of all possible demographic attributes.
Data Source
AI summary
The present invention is a method and system for characterizing physical space based on automatic demographics measurement, using a plurality of means for capturing images and a plurality of computer vision technologies. The present invention is called demographic-based retail space characterization (DBR). Although the disclosed method is described in the context of retail space, the present invention can be applied to any physical space that has a restricted boundary. In the present invention, the physical space characterization can comprise various types of characterization depending on the objective of the physical space, and it is one of the objectives of the present invention to provide the automatic demographic composition measurement to facilitate the physical space characterization. The demographic classification and composition measurement of people in the physical space is performed automatically based on a novel usage of a plurality of means for capturing images and a plurality of computer vision technologies on the captured visual information of the people in the physical space. The plurality of computer vision technologies can comprise face detection, person tracking, body parts detection, and demographic classification of the people, on the captured visual information of the people in the physical space.