Passthrough AR Mesh Transformation for Efficient Depth Reconstruction
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Solution Overview
Problem
Transforming high-resolution images from the viewpoint of see-through cameras to virtual rendering cameras in passthrough AR systems is computationally expensive and resource-intensive, particularly as camera resolutions increase.
Innovation Solution
Generate a mesh for each image with grid points at intersections, determine depths of these points, and transform the mesh from the see-through camera viewpoint to the user's viewpoint using sparse depth information, enabling efficient depth reconstruction and filtering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution images are transformed from see-through camera viewpoint to virtual rendering camera viewpoint using traditional methods, then rendering quality is maintained, but processing time and computational resources increase significantly
Solution Approach 1:
The patent segments the image transformation process into distinct stages: (1) generating a mesh representation of the scene from depth data, (2) transforming only the mesh vertices from camera viewpoint to rendering viewpoint using homography matrices, and (3) rendering the transformed mesh with texture mapping. This segmentation allows the computationally intensive pixel-level transformation to be replaced with efficient vertex-level transformation, significantly reducing processing time while maintaining rendering quality.
Solution Approach 2:
The patent creates a mesh copy of the scene geometry that can be transformed independently from the original high-resolution image data. By working with this mesh copy rather than the full-resolution pixel data, the system achieves viewpoint transformation with fraction of the computational cost, as the mesh contains only essential geometric information needed for rendering.
2Measurement precision
If traditional viewpoint transformation methods are used for high-resolution images, then accurate depth reconstruction is achieved, but memory consumption increases
Solution Approach 1:
The patent extracts only the essential depth information needed for transformation by generating a mesh from depth data and transforming only the mesh vertices. This extraction approach removes unnecessary pixel-level depth data from memory, keeping only the critical geometric information required for accurate viewpoint transformation and depth reconstruction.
Solution Approach 2:
The patent transitions from working with 2D image pixel coordinates to 3D mesh vertex coordinates in object space. By performing transformations in this alternative coordinate system (3D space rather than 2D image space), the system achieves accurate depth reconstruction with reduced memory requirements, as the mesh representation is inherently more compact than full-resolution depth maps.
3Productivity
If mesh transformation with depth reconstruction is implemented, then processing efficiency improves, but system complexity increases
Solution Approach 1:
The patent implements a universal mesh transformation pipeline that handles multiple rendering scenarios (different viewpoints, resolutions, and field-of-view angles) through a single homogeneous process. The same mesh generation, vertex transformation, and rendering steps work across all scenarios, eliminating the need for multiple specialized processing paths and reducing overall system complexity despite the added processing efficiency.
Data Source
AI summary
A method includes obtaining images of an environment captured by imaging sensors associated with a passthrough AR device and position data and depth data associated with the images. The method also includes generating a point cloud representative of the environment based on the images, position data, and depth data. The method further includes generating a mesh for a specified image. The mesh includes grid points at intersections of mesh lines. The method also includes determining one or more depths of one or more grid points of the mesh. The method further includes transforming the mesh from a viewpoint of a specified imaging sensor that captured the specified image to a user viewpoint of the passthrough AR device based on the depth(s) of the grid point(s). In addition, the method includes rendering a virtual view of the specified image for presentation by the passthrough AR device based on the transformed mesh.