Adaptive 3D Model Updates with Low-Resolution Scene Checks
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Solution Overview
Problem
The continuous generation and updating of high-resolution 3D models in augmented reality systems is computationally expensive due to the need for constant comparison of point clouds with high-resolution models, especially when objects in the scene change.
Innovation Solution
Segmenting the 3D model into regions and using simpler, lower-resolution models for comparison with aggregated point clouds to determine the need for updates, only updating the high-resolution model when significant differences are detected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous comparison of point clouds with high-resolution 3D model is performed, then accuracy of scene representation is maintained, but computational cost increases significantly
Solution Approach 1:
The patent segments the 3D model into multiple regions and performs comparison operations on segmented portions rather than the entire model. This allows the system to maintain accuracy by comparing point clouds with relevant model regions while reducing overall computational cost by processing smaller, divided segments instead of the complete high-resolution model continuously.
Solution Approach 2:
The patent applies different levels of model detail and comparison frequency to different regions based on their importance and change characteristics. High-priority regions with frequent changes receive more intensive comparison and updating, while low-priority static regions use simpler models and less frequent updates, optimizing the balance between accuracy and computational efficiency.
2Manufacturing precision
If high-resolution 3D model is continuously updated, then model accuracy is maintained, but processing time increases
Solution Approach 1:
The patent implements periodic update strategies where the 3D model is updated at different intervals based on region characteristics. Instead of continuous updating, the system performs comparisons and updates periodically, with frequency adjusted according to region priority and detected change levels, thereby reducing processing time while maintaining necessary model accuracy.
Solution Approach 2:
The patent divides the model into regions that can be updated independently and selectively. By segmenting the model, the system updates only specific regions that require changes rather than the entire model, significantly reducing processing time while maintaining accuracy in critical areas through targeted updates.
3Power
If simpler lower-resolution models are used for comparison, then computational overhead is reduced, but detection precision of changes decreases
Solution Approach 1:
The patent uses simpler lower-resolution models for initial comparison operations in regions where high precision is not critical, reducing computational overhead. Meanwhile, it maintains higher-resolution models and more precise comparison methods for regions requiring accurate change detection, thereby optimizing the balance between computational efficiency and detection precision through localized quality adjustment.
Solution Approach 2:
The patent segments the scene into regions that are compared against appropriately resolution-matched model portions. By dividing the comparison task into segmented operations, the system can use simpler models for large-area static regions (reducing computational overhead) while applying more precise comparison methods to smaller dynamic regions (maintaining detection precision).
Data Source
AI summary
In one embodiment, a computing system may update a first 3D model of a region of an environment based on comparisons between the first 3D model and first depth measurements of the region generated during a first time period. The computing system may determine that the region is static by comparing the first 3D model to second depth measurements of the region generated during a second time period. The computing system may in response to determining that the region is static, detect whether the region changed after the second time period based on comparisons between a second 3D model of the region and third depth measurements of the region generated after the second time period, the second 3D model having a lower resolution than the first 3D model. The computing system may in response to detecting a change in the region, update the first 3D model of the region.