Radar-Based Sign Language Interpretation Without External Light
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Solution Overview
Problem
Conventional technologies for sign language recognition, such as video and wearable sensors, face limitations in low-light conditions and privacy concerns, and are not practical for emergency situations or personal spaces, hindering effective communication for the Deaf community.
Innovation Solution
The use of radar technology to detect and interpret sign language gestures without external illumination, enabling 360-degree recognition and fusion with 3D video imagery for accurate linguistic communication, with output in visual or audible formats through a computing device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If video-based systems are used for sign language recognition, then recognition accuracy can be achieved, but the system cannot work during the night or in dark spaces due to requiring external light source
Solution Approach 1:
The patent replaces the optical-mechanical video-based detection system with a radar-based electromagnetic detection system. Radar uses radio frequency electromagnetic waves to detect hand gestures and body movements, eliminating the need for external light sources and enabling operation in complete darkness. The radar system transmits electromagnetic signals that reflect off the user's body and hands, capturing motion patterns for sign language recognition without requiring any illumination.
2Ease of operation
If video cameras are used for sign language recognition, then communication can be enabled, but private visual images may be captured, precluding use in personal spaces
Solution Approach 1:
The patent substitutes video camera-based optical detection with radar-based electromagnetic detection. Radar systems detect only motion patterns and spatial positions of body parts, not visual images. The radar data captures hand gestures, arm movements, and body orientation necessary for sign language recognition but does not capture facial features, clothing details, or other personally identifiable visual information, thereby preserving user privacy while enabling communication.
Solution Approach 2:
The patent extracts only the essential motion-related information from the detection process. Instead of capturing complete visual scenes with video cameras, the radar system selectively detects and processes only the spatial-temporal patterns of hand and body movements. This extraction of motion data while discarding visual image data enables sign language recognition without capturing private visual information.
3Measurement precision
If wearable sensors are used for sign language recognition, then gesture detection accuracy is improved, but it is not practical to always carry or wear the sensors when needed
Solution Approach 1:
The patent uses radar to create a non-contact digital model or 'copy' of the user's hand gestures and body movements. Instead of requiring physical sensors attached to the user's body, the radar system remotely captures motion patterns and reconstructs gesture information in digital form. This copying approach achieves gesture recognition accuracy comparable to wearable sensors while eliminating the need for the user to physically carry or wear any devices.
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
Radar-based systems provide reliable and private sign language interpretation in various environments, overcoming the limitations of existing technologies by enabling communication without the need for external lighting and offering flexible output formats.
Implementation Method 1
Radar, as described herein, possesses unique advantages that can be used to enable interpretation of sign language in situations where video cannot be used or performance is limited. Radar is a sensor that can detect patterns of motion, without acquiring private images.
Implementation Method 2
Radar estimates the distance to an object by measuring the time it takes for the transmitted signal to reach the object and return, and the instantaneous velocities and accelerations of different parts of moving objects by measuring the time-dependent frequency shifts of the wave scattered by the object, known as the Doppler effect.
Data Source
AI summary
Disclosed herein are methods, apparatus and computer program product for radar-based communication and interpretation of sign languages such as American Sign language (ASL) comprising detecting, using a radar system comprising a computing device, sign language gestures, wherein said detected sign language gestures comprise radar data; analyzing the radar data using a trained neural network executing on the computing device to determine word or phrases intended by the sign language gestures; and outputting the determined words or phrases in a visible or audible format.