AR Frame Processing Segmentation for Privacy and Efficiency
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Solution Overview
Problem
Current Augmented Reality (AR) technologies face challenges in providing high-bandwidth, low-latency experiences due to limitations in existing Internet Protocols, and raise privacy concerns with the use of AR devices that capture and process sensitive information, leading to security issues and restricted adoption.
Innovation Solution
The method involves dividing the processing of AR frames into private and non-private tasks, where private tasks are executed on trusted devices and non-private tasks on non-trusted devices, based on a user-defined privacy policy, to generate an overlay display that maintains user privacy while utilizing external computational resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If AR frame processing is distributed to non-trusted external devices to utilize external computational resources, then computational efficiency and productivity are improved, but user privacy and security are compromised due to exposure of sensitive frame data
Solution Approach 1:
The patent segments AR frame processing into private tasks (processed locally on trusted devices) and non-private tasks (processed on non-trusted external devices). This segmentation allows computational workload distribution to external devices while protecting sensitive information by keeping private processing local, thus resolving the contradiction between utilizing external resources and maintaining privacy.
Solution Approach 2:
The patent extracts and isolates private portions of AR frames that contain sensitive information, preventing their transmission to non-trusted devices. Only non-private portions are sent for external processing, thereby extracting the harmful element (privacy exposure) from the system while maintaining computational efficiency benefits.
2Object-affected harmful factors
If all AR frame processing is performed locally on trusted devices, then user privacy and security are maintained, but computational resources are insufficient leading to reduced productivity
Solution Approach 1:
The patent divides processing tasks into those that must remain local (private tasks) and those that can be offloaded (non-private tasks). This segmentation enables the system to maintain privacy protection for sensitive data while offloading computationally intensive non-private tasks to external devices, thus avoiding local resource bottlenecks.
Solution Approach 2:
The patent applies partial processing locally and partial processing externally, rather than requiring all processing to occur locally. This partial action approach allows the system to achieve sufficient computational capacity by leveraging external resources for non-critical portions while maintaining privacy through local processing of sensitive portions.
3Quantity of substance
If high-bandwidth networks are used to support AR streaming requirements, then data transmission capacity is improved, but latency remains insufficient for real-time AR experiences
Solution Approach 1:
The patent extracts and processes AR frame data locally without requiring complete transmission to remote servers. By keeping critical processing local and only transmitting necessary portions, the system reduces network dependency and achieves real-time performance without requiring extremely high bandwidth networks.
Solution Approach 2:
The patent performs preliminary processing of AR frames locally before any potential transmission, filtering and preparing data in advance. This preliminary action reduces the amount of data that needs network transmission and minimizes latency, enabling real-time AR experiences without requiring excessive network bandwidth.
Data Source
AI summary
Method, system and product for performing private and non-private tasks in Augmented Reality (AR) systems. A privacy policy of a user using an AR device is obtained. A frame sensor is utilized to obtain frames for processing. An overlay display for the frame is generated. The overlay display is generated based on an execution of a non-private task on a non-trusted device and based on an execution of a private task on a trusted device. The private task and the non-private task are determined based on the privacy policy. The overlay display is displayed by an AR device.