Multi-Aperture Visual Sensing for Sign Language Recognition
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Solution Overview
Problem
Existing sign language translation systems struggle to accurately capture and process the complexity of sign languages, which use hand movements, body cues, and facial expressions, often failing to provide natural translations due to their reliance on single sensors and processes.
Innovation Solution
The use of multiple visual and non-visual sensing devices with multiple apertures oriented to capture optical signals from multiple angles, generating digital information, collecting depth information, and combining it with environmental factors to create a composite digital representation for accurate sign language recognition and translation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If single sensor and process are used for sign language translation, then device complexity is reduced, but translation accuracy and naturalness deteriorate
Solution Approach 1:
The system divides the sensing function into multiple specialized sensors: visual sensors for hand gestures, non-visual sensors for environmental factors, and separate processing streams for different modalities. This segmentation allows each sensor to optimize for its specific function while collectively achieving comprehensive sign language recognition.
Solution Approach 2:
The system merges data from multiple sensors and processing streams into a unified translation output. By combining visual information from multiple angles, depth information, and environmental context, the system achieves accurate and natural sign language translation that no single sensor could provide alone.
2Measurement precision
If multiple apertures and sensing devices are used to capture from multiple angles, then recognition accuracy is improved, but device complexity increases
Solution Approach 1:
The multiple apertures and sensing devices are designed to perform multiple functions: capturing hand gestures, tracking body movement, detecting facial expressions, and sensing environmental factors. This multi-functionality justifies the increased device complexity by providing comprehensive data for accurate sign language recognition.
Solution Approach 2:
The system adds spatial dimensions by using multiple apertures oriented at different angles, capturing depth information, and collecting data from multiple planes. This dimensional expansion provides comprehensive 3D movement capture that significantly improves recognition accuracy despite increased device complexity.
3Reliability
If depth information and environmental factors are collected and combined, then translation robustness is improved, but processing complexity increases
Solution Approach 1:
The system introduces intermediate processing stages that integrate depth information and environmental factors before final translation. These intermediary processing layers combine multiple data streams in a structured manner, improving translation robustness while managing processing complexity through organized data integration.
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
This approach enables robust and accurate recognition and translation of sign languages, facilitating communication between different sign language users and between sign language and spoken languages, with the ability to adapt to various sign languages and environments.
Implementation Method 1
multiple apertures oriented with respect to the subject to receive optical signals corresponding to the at least one movement from multiple angles
Implementation Method 2
collecting depth information corresponding to the at least one movement in one or more planes perpendicular to an image plane captured by the set of visual sensing devices
Data Source
AI summary
Methods, apparatus and systems for recognizing sign language movements using multiple input and output modalities. One example method includes capturing a movement associated with the sign language using a set of visual sensing devices, the set of visual sensing devices comprising multiple apertures oriented with respect to the subject to receive optical signals corresponding to the movement from multiple angles, generating digital information corresponding to the movement based on the optical signals from the multiple angles, collecting depth information corresponding to the movement in one or more planes perpendicular to an image plane captured by the set of visual sensing devices, producing a reduced set of digital information by removing at least some of the digital information based on the depth information, generating a composite digital representation by aligning at least a portion of the reduced set of digital information, and recognizing the movement based on the composite digital representation.