AR Reference Frame Synchronization via Object Selection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current augmented reality technologies face challenges in synchronizing reference frames between multiple devices, leading to inefficiencies in collaborative experiences due to the need for extensive scanning and localization within three-dimensional environments.
Innovation Solution
A method that involves devices recording images, detecting objects, and estimating locations using odometry data and computer vision techniques to calculate reference vectors, allowing for the transformation of reference frames to a common frame, enabling synchronized augmented reality experiences without the overhead of extensive scanning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If extensive scanning and localization methods are used to synchronize reference frames between multiple devices, then measurement precision of device locations is improved, but loss of time and system complexity increase
Solution Approach 1:
The patent extracts the essential synchronization information by having users select only key reference objects from the environment, rather than scanning and processing all objects. This selective approach extracts the minimum necessary data to establish reference frame synchronization, significantly reducing processing time while maintaining adequate precision for collaborative AR experiences
Solution Approach 2:
The system performs preliminary actions by pre-establishing reference vectors between selected objects before the actual collaborative session begins. This preliminary setup includes calculating transformation matrices and establishing coordinate relationships in advance, so that when devices need to synchronize, the heavy computational work has already been completed
2Measurement precision
If extensive scanning and localization methods are used to synchronize reference frames between multiple devices, then measurement precision of device locations is improved, but device complexity increases
Solution Approach 1:
The patent segments the complex synchronization problem into manageable components: (1) object selection interface, (2) reference vector calculation between object pairs, (3) transformation matrix computation, and (4) coordinate frame alignment. Each component handles a specific aspect of the synchronization task, making the overall system more modular and manageable despite the complexity of achieving precise multi-device alignment
Solution Approach 2:
The patent introduces reference objects as intermediaries between devices. Instead of devices directly computing their relative positions, they both reference selected environmental objects and compute transformations through these intermediaries. This mediator approach simplifies the computational graph and makes the synchronization process more tractable
3Loss of time
If selective object-based reference frame synchronization is used, then loss of time is reduced, but measurement precision of device locations may deteriorate
Solution Approach 1:
The patent changes the parameter of reference frame establishment from comprehensive environmental scanning to selective object-based referencing. By transforming the approach to use only N key objects (where N is small) rather than all detectable objects, the system achieves faster synchronization while the transformation matrices computed from these selected objects maintain sufficient precision for the collaborative AR use case
Data Source
AI summary
A method includes: detecting an object in a first image; receiving a selection of the object depicted in the image; associating the object with a second device based on the selection; and, in response to the selection: recording a series of odometry data; estimating a location of the first device based on the odometry data; recording a series of images; estimating a location of the second device based on the images; calculating a first reference vector in the reference frame of the first device defining the location of the second device relative to the location of the first device; receiving, from the second device, a second reference vector; calculating a rotation and an offset between the reference vectors; and transforming the reference frame of the first device to a common reference based on the rotation and the offset.