XR Device Physical Object Context Extraction
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Solution Overview
Problem
Existing extended reality (XR) systems struggle to efficiently integrate physical objects, such as paper documents, into virtual environments, leading to decreased workflow efficiency and increased resource wastage due to manual searches and lack of digital representation.
Innovation Solution
A system that uses an extended reality device with a camera and machine learning models to detect physical objects, extract context information, and query a database to retrieve associated tasks and document objects, thereby augmenting the XR environment with digital overlays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual searching and handling of physical documents is used, then ease of operation is maintained, but productivity decreases and time is wasted
Solution Approach 1:
The system enables physical documents to effectively serve themselves by automatically detecting them through the camera, extracting their context information, and retrieving associated digital data without requiring manual intervention. The XR device autonomously processes documents in the user's field of view, converting physical artifacts into digital information seamlessly.
Solution Approach 2:
The patent replaces manual mechanical operations (physically searching for, handling, and processing documents) with an automated optical and computational system. The camera captures images, machine learning models extract information, and digital databases retrieve data, substituting human physical actions with automated technological processes.
2Productivity
If physical documents are integrated into virtual environments manually, then device complexity is reduced, but productivity decreases due to lack of automation
Solution Approach 1:
The XR device performs multiple functions through a single integrated system: it captures images with its camera, processes them through machine learning models, queries databases, and displays augmented information. This multi-functional approach consolidates what would otherwise require separate tools and manual coordination into one unified device.
Solution Approach 2:
The system introduces an intermediary layer between physical documents and digital information. The machine learning model acts as a mediator that extracts context from physical documents, enabling the system to bridge the physical and digital domains automatically without requiring manual intervention or complex integration procedures.
3Productivity
If automated detection and processing of physical objects is implemented, then productivity increases, but device complexity increases
Solution Approach 1:
The automated processing system is divided into distinct functional modules: camera capture, machine learning-based context extraction, database querying, and augmented display. Each module handles a specific task independently, making the overall complex system manageable through functional segmentation and modular architecture.
4Loss of information
If physical objects are not digitally represented, then device complexity is reduced, but loss of information occurs due to lack of digital integration
Solution Approach 1:
The system creates digital copies of physical document information by extracting context data and retrieving associated digital representations from databases. These digital copies are then overlaid on the physical documents in the XR environment, preserving and enhancing information accessibility without requiring physical document management.
Data Source
AI summary
In some implementations, there is a method provided that detects a physical object in a video stream provided by a camera of an extended reality device providing an extended reality environment; extracts context information from at least a portion of the video stream associated with the physical object; queries, using the extracted context information, a system including a database to obtain at least one task and/or at least one document object that are associated with the extracted context information; receives the at least one task and/or the at least one document object that are associated with the extracted context information; and provides to the head-mounted display the at least one task and/or the at least one document object to cause the extended reality device to augment, based on the extracted context information from the physical object, the extended reality environment. Related systems, methods, and articles of manufacture are also disclosed.