Virtual Feature Surface Reconstruction via Multi-Frame Raycast Selection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In mixed reality environments, the loss of spatial registration between virtual and physical elements due to shifting user perspectives can lead to inaccurate placement of virtual elements, degrading the user experience as feature points in physical user space become less reliable or lost.
Innovation Solution
A computing device spatially reconstructs a virtual feature surface by detecting and mapping feature points from multiple video frames into a virtual user space, selecting at least three feature points that satisfy specific criteria along a raycast axis, and defining the surface using these points, even if some points are missing from the current frame by utilizing buffered points from previous frames.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If feature points are tracked from multiple video frames to maintain spatial registration, then the reliability of virtual element positioning is improved, but the complexity of data processing and selection increases
Solution Approach 1:
The system performs preliminary detection and mapping of feature points from multiple video frames before the actual spatial reconstruction is needed. By pre-processing and buffering feature points from historical frames, the system prepares candidate points in advance, reducing the complexity of real-time selection while maintaining high spatial registration accuracy.
Solution Approach 2:
The system uses the device's own camera to capture video frames and automatically detects feature points without external assistance. The feature point selection process is self-contained, using buffered data from previous frames to independently determine the best points for spatial reconstruction, eliminating the need for external calibration or manual intervention.
2Measurement precision
If multiple feature points from different video frames are selected and mapped, then the accuracy of virtual feature surface definition is improved, but the loss of time for processing multiple frames increases
Solution Approach 1:
Feature points from multiple video frames are detected and mapped in advance to a buffer before the actual spatial reconstruction operation. This preliminary processing allows the system to have candidate points ready, reducing the time required during the actual surface definition operation while maintaining high accuracy through multi-frame data.
Solution Approach 2:
The system dynamically selects feature points based on their spatial distribution and quality metrics from the buffered data. Rather than processing all frames equally, the system adapts its selection to the specific geometric requirements of the raycast element, optimizing the balance between accuracy and processing time based on real-time conditions.
3Manufacturing precision
If feature points are selected based on strict selection criteria along the raycast axis, then the precision of virtual element placement is improved, but the quantity of available feature points decreases
Solution Approach 1:
The system buffers feature points from multiple video frames in advance, creating a larger pool of candidate points before selection. This preliminary accumulation ensures that even when strict selection criteria are applied along the raycast axis, there are sufficient qualifying points available from the expanded temporal dataset to maintain both precision and adequate quantity.
Solution Approach 2:
The system extends the feature point selection from a single spatial dimension to multiple dimensions by incorporating temporal information from multiple video frames. This adds the time dimension to the selection process, allowing the system to find suitable feature points that satisfy selection criteria by searching across both spatial and temporal domains, thus maintaining precision while preserving quantity.
Data Source
AI summary
A computing device spatially reconstructs a virtual feature surface in a mixed reality environment. The computing device detects addition of a raycast element to a virtual user space, maps multiple feature points detected from multiple video frames of a physical user space into a virtual user space, selecting at least three feature points from the multiple feature points that satisfy selection criteria applied in the virtual user space along a raycast axis of the raycast element in the virtual user space, and defines the virtual feature surface in the virtual user space using the at least three selected feature points. At least two of the at least three feature points are detected in different video frames.