User Posture Detection Using Body Contour Pixel Distribution
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Solution Overview
Problem
Existing image detection technologies face challenges in accurately determining a user's posture, especially when facial features are unstable or obscured, leading to lower detection rates and efficiency.
Innovation Solution
An image detection method and device that utilizes body features like the trunk or limbs for analysis, calculating pixel accumulation values to perform pixel distribution analysis, allowing for precise determination of posture even when the face is not identifiable.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If facial features are used for posture detection, then detection rate is improved in clear visibility conditions, but detection reliability deteriorates when face is covered or features are unstable
Solution Approach 1:
The patent changes the detection parameter from facial features to body contour features. By extracting silhouette information and key point coordinates from the body contour instead of relying on facial features, the system maintains detection accuracy while improving reliability in conditions where the face is covered or facial features are unstable.
2Device complexity
If only facial features are used for detection, then detection process is simple, but detection efficiency deteriorates when face is obscured
Solution Approach 1:
The patent makes the detection system universal by using body contour features that work in both clear and obscured conditions. The same detection framework processes both facially-visible and face-obscured cases uniformly through contour extraction and key point analysis, maintaining efficiency across different scenarios without requiring separate detection pathways.
3Reliability
If body features are used instead of facial features, then detection reliability is improved when face is covered, but detection complexity increases
Solution Approach 1:
The patent segments the body contour detection process into distinct steps: obtaining the contour, extracting key points (head, shoulders, hips, knees, ankles), calculating coordinates, and determining posture. This segmentation simplifies the complex task of body feature analysis by breaking it into manageable, systematic operations that can be processed efficiently.
Data Source
AI summary
An image detection method for determining the posture of a user includes: obtaining a reference image of the user in a region of interest (ROI); obtaining a test image of user at the ROI; executing a feature matching analysis of the test image which compares the feature parameter of the test image and the feature parameter of the reference image to determine the similarity information of the test image and the reference image; and executing a pixel distribution analysis of the test image to obtain user pixel distribution information; and determining the posture of the user based on the user similarity information and the user pixel distribution information.