AR Anchor Reticle Using Virtual Tether for Planar Alignment
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Solution Overview
Problem
Placing computer-generated content in augmented reality scenes to appear in direct contact with real physical planar surfaces is challenging due to the lack of context regarding size, height, and distance within standard RGB imagery, as there is no inherent ground-truth information to determine the position and orientation of digital objects relative to physical surfaces.
Innovation Solution
A mobile image capture device captures images, determines a ground plane and wall plane, generates a guide reticle model at the intersection of these planes, and links a virtual tether to digital objects, allowing them to be rendered correctly relative to the physical environment without requiring pre-defined feature maps or additional hardware like depth sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If standard RGB imagery is used for augmented reality placement, then device complexity is reduced, but measurement precision of position and orientation relative to physical surfaces deteriorates
Solution Approach 1:
The patent introduces an intermediary coordinate transformation system that maps 2D image coordinates to 3D world coordinates through a virtual camera model. This intermediary framework enables precise measurement of digital object positions and orientations relative to physical surfaces without requiring complex depth sensing hardware, thus resolving the contradiction between device simplicity and measurement precision.
Solution Approach 2:
The patent replaces mechanical/physical depth sensing systems with a computational approach using 2D image analysis and virtual camera geometry. By substituting physical depth cameras with mathematical coordinate transformations based on known camera intrinsics and detected surface geometry, the system achieves precise measurement without additional hardware complexity.
2Manufacturing precision
If depth cameras are used to determine intersection between computer generated content and physical objects, then manufacturing precision of placement is improved, but device complexity increases
Solution Approach 1:
The patent creates a virtual copy of the camera's coordinate system and projection geometry to calculate where digital objects should intersect with physical surfaces. By using a virtual camera model that replicates the real camera's optical properties, the system achieves precise placement calculations using only 2D image data, avoiding the need for physical depth cameras while maintaining manufacturing precision.
Solution Approach 2:
The patent transforms the problem from 3D depth measurement to 2D geometric parameter analysis. By changing the approach from measuring physical depth directly to calculating intersection points through coordinate transformations and surface detection in 2D image space, the system achieves precise placement without requiring depth sensing hardware, thus improving placement precision while reducing device complexity.
3Measurement precision
If ground-truth information is extracted from image data to determine position and orientation, then measurement precision is improved, but difficulty of detecting and measuring increases
Solution Approach 1:
The patent performs preliminary establishment of a virtual camera coordinate system and projection model before attempting to measure digital object positions. By pre-defining the geometric relationship between the camera, image plane, and 3D world coordinates, the system simplifies the subsequent measurement process, making it easier to extract ground-truth information about position and orientation from 2D image data.
Solution Approach 2:
The patent solves the measurement difficulty by introducing a virtual 3D coordinate system that projects onto the 2D image plane. This dimensional transformation allows the system to measure position and orientation in 3D space while working with 2D image data, effectively converting a difficult 3D measurement problem into a manageable 2D-to-3D coordinate transformation problem with known geometric relationships.
Data Source
AI summary
Devices, systems, and methods may implement one or more techniques for anchoring computer generated objects within an augmented reality scene. One or more techniques may include capturing an image frame via a camera sensor, for example. One or more techniques may include determining a ground plane of the image frame and/or identifying a wall plane of the image frame. One or more techniques may include generating a model of a guide reticle and/or linking a virtual tether connecting the guide reticle to a digital object to be rendered relative to the guide reticle. One or more techniques may include rendering the guide reticle and the virtual tether to a display of, for example, a mobile image capture computing device relative to the wall plane and the ground plane. One or more techniques may include rendering the digital object to the display relative to the guide reticle and the virtual tether.