Scene Model Generation via Ray Casting and Caching
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Solution Overview
Problem
Existing artificial reality systems face challenges in efficiently generating, querying, and managing scene models, particularly in handling localization failures that lead to relocalization issues and frustration for users.
Innovation Solution
The system introduces a scene model that is an objective, system-managed representation of a user's physical environment, composed of anchors that describe static geometry and semantics. This scene model is generated using a scene capture workflow, and a scene realignment solution is provided to mitigate localization failures by relying on user input to align cached room data with the current map.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the system uses automated scene capture workflows to generate scene models, then productivity is improved, but reliability deteriorates due to localization failures and relocalization issues
Solution Approach 1:
The system performs preliminary scene capture and caching during initial setup or when the environment is stable. By capturing and storing scene data in advance (creating a cached scene model), the system prepares reliable reference data before potential localization failures occur, enabling faster recovery without re-scanning the entire environment.
Solution Approach 2:
The system creates and maintains cached copies of scene models that can be reused when the current localization fails. Instead of relying solely on real-time sensor data, the system references previously captured and stored scene representations, allowing it to recover from localization errors without requiring complete re-capture of the environment.
2Measurement precision
If the system implements comprehensive scene capture workflows to capture all environment details, then measurement precision is improved, but loss of time increases due to extensive re-scanning when relocalization is needed
Solution Approach 1:
The system performs comprehensive environment capture and stores detailed scene models in cache during initial setup. This preliminary action ensures high measurement precision is achieved once, and the cached data can be reused multiple times without requiring re-scanning, thus eliminating the time loss that would otherwise occur during relocalization events.
Solution Approach 2:
When localization failures occur, the system recovers by referencing previously captured and cached scene data instead of discarding the original comprehensive capture effort. The cached representations serve as recoverable copies that maintain high measurement precision without requiring time-consuming re-scanning of the entire environment.
3Object-affected harmful factors
If the system manages detailed scene models with multiple anchors and components, then object-affected harmful factors are reduced through better environment understanding, but device complexity increases
Solution Approach 1:
The scene model is segmented into discrete anchors, each representing specific environmental features or objects. This segmentation allows the system to manage complexity by breaking down the overall scene into manageable components, where each anchor can be independently captured, stored, and referenced, reducing the impact of localization failures on the entire scene.
Solution Approach 2:
The system maintains cached copies of the segmented scene model structure, allowing it to recover from localization failures by referencing previously stored anchor data. This approach manages the complexity of detailed scene models by providing a recoverable snapshot that can be restored without re-capturing the entire complex structure.
Data Source
AI summary
In particular embodiments, a computing system may initiate a scene capture process to capture a scene. The scene may include one or more of planes or objects. The system may send a first set of instructions to outline one or more planes of the scene. The system may cast a first set of rays to outline the one or more planes. The system may create the one or more planes based on the first set of rays. The system may send a second set of instructions to outline one or more objects of the scene. The system may cast a second set of rays to outline the one or more objects. The system may create the one or more objects based on the second set of rays. The system may generate a scene model of the scene based on the one or more planes and the one or more objects.