Vision-Based Posture Detection Using Key Point Correlation
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Solution Overview
Problem
Existing systems lack an efficient and automated method to detect poor postures in children, which can lead to crooked bone development and decreased concentration due to inadequate oxygen intake, posing a burden on supervisors to constantly monitor proper sitting and standing postures.
Innovation Solution
An intelligent posture detection system using vision sensing technology and machine learning algorithms to analyze images for key points and geometric relationships, determining if a person is in a poor posture by establishing correlations between key points and an object window, and providing notifications when thresholds are exceeded.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual monitoring of children's posture is performed by parents or teachers, then posture can be detected, but the burden on supervisors increases and continuous monitoring is laborious
Solution Approach 1:
The system enables automatic self-monitoring of posture through vision sensing technology and machine learning algorithms. The intelligent model automatically detects key points, establishes correlations, and determines poor posture without requiring manual intervention from parents or teachers, thus eliminating the laborious task of continuous manual monitoring while maintaining accurate posture detection
Solution Approach 2:
The patent replaces the mechanical manual monitoring system with an automated vision-based detection system. Instead of human supervisors physically observing and reminding children, the system uses image retrieval circuits, image processors, and intelligence models to automatically detect and analyze posture, substituting mechanical human effort with automated technological systems
2Extent of automation
If vision sensing technology with intelligence models is used to automatically detect posture, then the burden on supervisors is reduced, but the device complexity increases
Solution Approach 1:
The system divides the complex posture detection task into distinct functional modules: an image-retrieval circuit for capturing images, an image processor for extracting features, and an operating circuit with an intelligence model for analysis. This segmentation allows each component to perform a specific function, managing overall system complexity through modular design while achieving high automation
Solution Approach 2:
The patent introduces an intelligence model as an intermediary between raw image data and posture determination. The model acts as a mediator that processes image features, defines object windows, identifies key points, and establishes correlations automatically. This intermediary layer simplifies the automation process by handling the complex analysis tasks centrally while keeping other system components relatively simple
Data Source
AI summary
A method for intelligent posture detection, an intelligent posture detection apparatus, and a circuit system are provided. The circuit system is disposed in the intelligent posture detection apparatus, and the method is performed in the circuit system. In the method, the circuit system retrieves an image from an image-retrieval circuit, and operates an intelligence model by an operating circuit for determining an object window that covers an object in the image and multiple key points of the object. Next, a first correlation among a whole or part of the key points of a current posture of the object, and a second correlation between the object window and the whole or part of the key points are established. The first correlation, the second correlation, and/or geometric information of the object window can be referred to for determining whether or not the current posture of the object is poor.