Dual Analysis Image Detection for User Positioning
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Solution Overview
Problem
Existing image detection methods for determining user positions, such as those for monitoring babies, children, patients, or elderly individuals, face challenges due to unstable facial features and discomfort or inefficiency from wearable devices, leading to low detection rates and power issues.
Innovation Solution
An image detection method utilizing an artificial intelligence neural network for dual analysis of body distribution and face occlusion, which involves obtaining feature parameters from images, performing region-based analyses, and adjusting confidence levels to accurately determine user positions, even in cases where facial features are obscured.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If facial features are used for position determination, then detection rate is improved when frontal face is visible, but detection rate deteriorates significantly when lateral face is detected
Solution Approach 1:
The patent segments the face into multiple regions (frontal face region, lateral face region, occluded face region) and applies different detection strategies to each region. This allows the system to handle various face orientations and occlusion levels effectively, improving overall detection reliability across different scenarios.
Solution Approach 2:
The patent changes detection parameters based on the detected face region and occlusion level. When frontal face is detected, one set of parameters is used; when lateral face or occluded face is detected, parameters are adjusted accordingly. This dynamic parameter adjustment maintains detection accuracy across varying conditions.
2Measurement precision
If smart wearable devices are used to obtain physiological information, then information accuracy is improved, but power consumption increases and user comfort deteriorates
Solution Approach 1:
The patent replaces the mechanical wearable device system with an optical/image-based detection system. Instead of using sensors embedded in wearable devices that consume power continuously, the system uses image processing algorithms to extract physiological information, eliminating power consumption issues while maintaining detection accuracy.
Solution Approach 2:
The patent creates a virtual model of physiological information from image data rather than direct sensor measurement. By analyzing facial images to infer physiological states, the system obtains the necessary information without requiring physical contact or power-intensive wearable sensors.
3Measurement precision
If smart wearable devices are used for detection, then detection capability is improved, but user comfort and convenience deteriorate
Solution Approach 1:
The patent enables the detection system to work passively without requiring user action or wearing devices. The system automatically captures and processes images to determine position and physiological information, making the detection process invisible and comfortable for users while maintaining high detection capability.
Data Source
AI summary
An image detection method is provided. In the image detection method, images of a user are obtained, feature parameters are marked in the images, and detection results of the feature parameters in each of the images are evaluated. A body distribution analysis is performed on the images according to the detection result of at least one first feature parameter among the feature parameters to determine first position information of the user. A face occlusion analysis is performed on the images according to the detection result of at least one second feature parameter among the feature parameters and the first position information to determine second position information of the user. The at least one second feature parameter is different from the at least one first feature parameter. The second position information represents a position of the user.