Radar Gesture Recognition Using Echo Filtering by Distance, Speed, and Angle
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Solution Overview
Problem
Conventional gesture recognition technologies face limitations such as poor performance in varying light conditions, reliance on line of sight, high storage and computing costs, and privacy leakage risks, particularly in optical-based systems.
Innovation Solution
A gesture recognition method using millimeter-wave radar to filter echo data by dimensions like speed, distance, and angle to obtain accurate gesture data, reducing interference and privacy risks, enabling recognition in various lighting conditions with reduced computational demands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If optical camera is used for gesture recognition, then gesture shape can be clearly indicated, but performance deteriorates in strong light or dim light conditions
Solution Approach 1:
The patent replaces the optical camera-based recognition system with a radar-based detection system. The radar uses electromagnetic wave reflection to detect gesture movements, completely avoiding dependency on visible light conditions. This substitution enables reliable gesture recognition in both strong light and dim light environments while maintaining measurement precision through multidimensional parameter detection.
2Measurement precision
If optical camera is used for gesture recognition, then gesture can be recognized, but line of sight is highly demanded and obstacles cannot exist between camera and hand
Solution Approach 1:
The patent substitutes optical line-of-sight detection with radar electromagnetic wave detection. Radar waves can penetrate through certain obstacles and reflect off the target object regardless of direct line of sight requirements. This enables gesture recognition even when obstacles exist between the radar and the user's hand, significantly improving operational flexibility while maintaining recognition accuracy.
3Loss of information
If optical image is used for gesture recognition, then gesture information can be obtained, but storage costs and computing costs are high
Solution Approach 1:
The patent extracts only the essential gesture-related parameters (distance, speed, angle) directly from radar echo data, eliminating the need to process and store large volumes of optical image data. By directly detecting physical movement parameters through radar, the system obtains sufficient gesture information with dramatically reduced data storage requirements and computational processing costs.
4Measurement precision
If facial image is obtained during gesture recognition according to optical principle, then gesture can be recognized, but privacy leakage risk increases
Solution Approach 1:
The patent replaces optical facial image capture with radar-based gesture detection. The radar system only detects physical movement parameters such as distance, speed, and angle of hand gestures, completely avoiding capture of facial images or other personal identifiable information. This substitution maintains gesture recognition capability while eliminating privacy leakage risks associated with facial image processing.
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
The method achieves accurate and efficient gesture recognition, including subtle movements, without privacy concerns, and allows for user control in diverse environments, enhancing user experience.
Implementation Method 1
obtaining echo data of a radar, where the echo data includes information generated when an object moves in a detection range of the radar
Data Source
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AI summary
This application discloses a gesture recognition method and apparatus, to filter echo data in a dimension such as a speed, a distance, or an angle, to obtain gesture data with less interference. This can accurately recognize a gesture of a user, and improve user experience. The method includes: obtaining echo data of a radar, where the echo data includes information generated when an object moves in a detection range of the radar; filtering out, from the echo data, information that does not meet a preset condition, to obtain gesture data, where the preset condition includes at least two of a distance, a speed, or an angle, the distance includes a distance between the object and the radar, the speed includes a speed of the object relative to the radar, and the angle includes an azimuth or a pitch angle of the object in the detection range of the radar; extracting a feature from the gesture data, to obtain gesture feature information; and obtaining a target gesture based on the gesture feature information.