Collaborative AR Sign Recognition for Low-Power Translation
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Solution Overview
Problem
Existing augmented reality (AR) devices face challenges in efficiently translating sign language due to resource management limitations, particularly in processing power and computational load, which can lead to inefficiencies and increased power consumption.
Innovation Solution
A collaborative system of AR devices, where one device captures hand gestures and another performs computational-intensive tasks like hand tracking and gesture recognition, distributing processes to optimize resource utilization and reduce power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a single AR device performs all sign language translation processes locally, then translation speed is improved, but power consumption and computational load increase
Solution Approach 1:
The patent divides the sign language translation system into multiple functional segments distributed across different AR devices. One device captures hand gestures while another performs computational-intensive tasks like hand tracking and gesture recognition. This segmentation allows each device to perform only its designated function, reducing overall power consumption while maintaining translation speed through coordinated operation.
Solution Approach 2:
The patent introduces a collaborative framework where AR devices act as intermediaries to each other. Instead of one device bearing the entire computational burden, devices coordinate by capturing, sharing, and processing visual data together. This intermediary collaboration distributes the computational load and reduces individual device power consumption while achieving real-time translation.
2Measurement precision
If computational-intensive tasks are performed on a single device, then translation accuracy is improved, but device complexity and resource requirements increase
Solution Approach 1:
The patent segments complex computational tasks across multiple devices. Hand tracking is performed by one device while gesture recognition and translation are handled by another. This division maintains translation accuracy by ensuring each device focuses on its specialized function rather than attempting to perform all processing locally, thereby reducing individual device complexity requirements.
Solution Approach 2:
The patent merges the capabilities of multiple AR devices into a unified collaborative system. By combining the computational resources of multiple devices working together, the system achieves translation accuracy that would require excessive resources on a single device, while distributing the actual computational burden across the network.
3Loss of time
If all processing is done locally on the AR device, then response time is reduced, but energy efficiency deteriorates
Solution Approach 1:
The patent segments processing tasks and assigns them to different devices based on their capabilities and current workload. Simple tasks like hand gesture capture are performed locally with minimal processing, while energy-intensive tasks are offloaded to collaborating devices. This segmentation maintains fast response times through coordinated processing while significantly improving overall energy efficiency by avoiding redundant computations on a single device.
Data Source
AI summary
A method for recognizing sign language using collaborative augmented reality devices is described. In one aspect, a method includes accessing a first image generated by a first augmented reality device and a second image generated by a second augmented reality device, the first image and the second image depicting a hand gesture of a user of the first augmented reality device, synchronizing the first augmented reality device with the second augmented reality device, in response to the synchronizing, distributing one or more processes of a sign language recognition system between the first and second augmented reality devices, collecting results from the one or more processes from the first and second augmented reality devices, and displaying, in near real-time in a first display of the first augmented reality device, text indicating a sign language translation of the hand gesture based on the results.