Pre-scanning and Indexing Nearby Objects in AR Headsets
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional methods for importing real-world objects into artificial reality environments are inefficient, requiring users to prioritize objects and endure long processing times, and often rely on cumbersome scanning processes.
Innovation Solution
The system allows users to pre-scan and index nearby objects during the loading of an artificial reality headset, associating scanned objects with weights and non-fungible token identities, enabling efficient importation of relevant objects into the AR environment without extensive scanning or processing delays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users manually prioritize and scan objects before importing into artificial reality, then object importation can be controlled, but the process requires long processing periods and user effort
Solution Approach 1:
The system performs preliminary scanning and indexing of objects in the environment when the artificial reality device is first powered on, before the user needs to import any objects. This preliminary action creates a ready-to-use database of scanned objects with associated weights, eliminating the need for users to manually prioritize objects later and significantly reducing processing time during actual import operations.
2Quantity of substance
If the system scans all objects in the environment, then complete object databases are created, but processing burden and time increase significantly
Solution Approach 1:
The system assigns different weights to different objects based on their importance to the user and the artificial reality experience. This local quality approach means that not all objects are treated equally - high-weight objects receive priority processing and are more likely to be imported, while low-weight objects can be processed later or excluded, reducing the immediate processing burden while maintaining database completeness.
3Manufacturing precision
If the system requires users to prioritize objects manually, then importation precision is improved, but ease of operation decreases
Solution Approach 1:
The system automatically performs object prioritization by assigning weights based on predefined criteria such as object frequency of use, relevance to current artificial reality experiences, and user preferences. This self-service mechanism eliminates the need for users to manually prioritize each object, maintaining high selection accuracy through automated intelligence while dramatically improving ease of operation.
Data Source
Figure 1
Figure 2A
Figure 2B
AI summary
Methods, systems, and storage media for scanning and indexing are disclosed. Exemplary implementations may: power on a headset; in response to the powering on, initiate a scan of an area; receive a request to include and/or exclude objects in the area from being scanned; associate scanned objects with a weight; and render the scanned objects through the headset.