Sitting Posture Detection Using Face Angles and Skeletal Coordinates
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Solution Overview
Problem
Conventional methods rely on visual observation for detecting sitting postures, which is often inaccurate, leading to health issues from prolonged unhealthy sitting habits.
Innovation Solution
A sitting posture detection apparatus and method that utilizes a processor to execute a program code, including a face and human identification module, face angle estimation module, and body posture estimation module to calculate face angles and bone feature point coordinates, generating standard sitting posture data for accurate determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple lenses are used to detect sitting posture, then detection precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent divides the detection task into separate modules: face detection module, body posture detection module, and angle calculation module. Each module processes specific aspects independently, achieving comprehensive posture detection without requiring multiple physical lenses, thus reducing device complexity while maintaining detection precision.
Solution Approach 2:
The detection system is designed to perform multiple functions using a single imaging device: it detects both facial orientation and body posture, calculates multiple angles (pitch, roll, yaw), and provides comprehensive posture assessment. This multi-functionality eliminates the need for separate detection systems, reducing overall device complexity.
2Measurement precision
If multiple lenses are used to detect sitting posture, then detection precision is improved, but cost increases
Solution Approach 1:
The patent segments the detection functionality into software modules rather than requiring multiple physical lenses. The face detection module, body posture detection module, and angle calculation module work together to provide comprehensive detection using a single imaging device, significantly reducing manufacturing cost while maintaining precision.
Solution Approach 2:
The system uses computational methods to create virtual detection capabilities through algorithm processing. Instead of physically copying detection functions with multiple lenses, the patent uses software-based face and body detection algorithms that process images from a single lens, achieving the same detection precision at lower cost.
3Device complexity
If visual observation is used to detect sitting posture, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent replaces manual visual observation with an automated computer vision system. The imaging device captures images, and software modules automatically detect facial features, body posture, and calculate angles, eliminating the need for human visual judgment while providing objective, precise measurements of sitting posture.
Solution Approach 2:
The system enables self-monitoring of sitting posture without requiring external observers or complex medical equipment. The imaging device and processing modules work autonomously to detect and analyze posture, providing immediate feedback that helps users self-correct their sitting habits.
Data Source
AI summary
A sitting posture detection method includes: identifying an input image to generate a face frame under detection and a human frame under detection of a person under detection; calculating a plurality of face angles of the face frame under detection; calculating a plurality of bone feature point coordinates of the human frame under detection; and generating standard sitting posture data according to the face angles and the bone feature point coordinates, and determining a sitting posture of the person under detection according to the face angles, the bone feature point coordinates and the standard sitting posture data.