Facial Video Blood Flow Detection Using RGB Fluctuation Analysis
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Solution Overview
Problem
Existing methods for detecting autonomic nervous activity using thermal facial images require specialized equipment like far-infrared cameras, making it difficult to detect blood flow accurately and economically.
Innovation Solution
A biometric detection system that processes video data of facial images to detect blood flow and activity by averaging pixel colors, particularly using (R−B) components to analyze fluctuations in the nose region, eliminating the need for specialized equipment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a far-infrared camera is used to acquire thermal images for detecting autonomic nervous activity, then the detection accuracy of blood flow changes is improved, but the device complexity and cost increase significantly
Solution Approach 1:
The patent uses a standard camera to capture visible light images of the face, creating a visual copy that contains blood flow information through color changes. This visible light copy replaces the need for specialized far-infrared thermal imaging, achieving blood flow detection without requiring expensive specialized equipment while maintaining detection capability through RGB color analysis
Solution Approach 2:
The patent substitutes the thermal radiation detection mechanism (far-infrared camera) with an optical reflection detection mechanism (standard camera capturing visible light). By analyzing color changes in the visible spectrum, particularly the (R-B) component, the system replaces complex thermal imaging hardware with a simple standard camera system that can infer blood flow from color variations
2Reliability
If thermal image processing is used to detect autonomic nervous activity, then the detection capability is improved, but the cost of the system increases due to specialized equipment requirements
Solution Approach 1:
The patent employs a standard camera, which is a inexpensive and widely available device, replacing the expensive far-infrared camera. The system uses readily accessible consumer electronics rather than specialized medical or scientific equipment, dramatically reducing the cost barrier while maintaining the ability to detect autonomic nervous activity through color analysis of facial images
3Measurement precision
If the nose region is analyzed for blood flow detection, then the accuracy of autonomic nervous activity detection is improved, but the system requires precise region localization which increases complexity
Solution Approach 1:
The patent applies periodic smoothing processing at regular time intervals to the RGB values in the nose region. This temporal averaging filters out noise and highlights periodic blood flow patterns, improving detection accuracy without requiring complex spatial localization algorithms. The periodic nature of blood flow provides a natural signal that can be extracted through simple temporal filtering
Solution Approach 2:
The patent focuses analysis specifically on the nose region, which has high sensitivity for detecting autonomic nervous activity changes. By concentrating computational resources on this specific local area rather than processing the entire face, the system achieves high detection accuracy with minimal processing complexity. The nose region's unique physiological characteristics make it an optimal focal point for blood flow detection
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Accurately detects autonomic nervous activity, such as stress, without specialized devices, by analyzing (R−B) components, providing stable and cost-effective detection of blood flow fluctuations.
Implementation Method 1
video data of a facial image captured of the face of a target person
Implementation Method 2
camera to acquire a still image or a moving image
Data Source
AI summary
Included are: an averaging processing unit configured to acquire video data of a facial image captured of a face of a target person and average all pixels in a specific region of the acquired video data, at regular time intervals, in terms of a difference component between color components of primary colors in the specific region; a fluctuation acquisition unit configured to obtain a fluctuation in each of the color components of the primary colors averaged by the averaging processing unit; and a detection unit configured to detect a blood flow or an activity based on the blood flow on the basis of an amount of fluctuation obtained by the fluctuation acquisition unit. This makes it possible to easily, in a non-contact manner, highly accurately detect the blood flow and detect an activity such as an autonomic nervous activity without preparing a special device.