3D Reference Surface Models for Precise AR Location Tracking
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Solution Overview
Problem
Existing augmented reality (AR) systems face challenges in seamlessly integrating computer-generated enhancements with real-world images, requiring complex image capture and matching processes to achieve a unified perspective.
Innovation Solution
A method for creating custom 3D models of static features or objects using Simultaneous Localization And Mapping (SLAM) tracking and 3D mesh models, aligned with each other, allowing users to generate and share AR experiences that can be triggered at specific locations using LIDAR technology.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex image capture and matching processes are used to integrate computer-generated enhancements with real-world images, then the quality and accuracy of AR rendering is improved, but the device complexity and processing requirements increase
Solution Approach 1:
The system performs preliminary actions by pre-processing images to identify and extract planar surfaces before AR rendering. This preliminary segmentation and surface detection creates a structured foundation that simplifies subsequent matching and rendering processes, reducing overall system complexity while maintaining accuracy
Solution Approach 2:
The image processing is segmented into distinct stages: initial image capture, planar surface identification, surface segmentation, and AR rendering. This segmentation allows each component to be optimized independently, managing complexity through modular processing steps rather than a monolithic complex system
2Measurement precision
If detailed 3D models and location tracking data are collected and processed, then the precision of AR experience delivery is improved, but the data processing time and computational resources increase
Solution Approach 1:
The system extracts only the essential and relevant data elements needed for AR rendering - specifically planar surface characteristics and their spatial relationships - rather than processing complete detailed 3D models of all objects. This extraction approach maintains location tracking precision while significantly reducing data processing requirements and time
Solution Approach 2:
The system performs partial action by focusing computational resources on processing only the planar surfaces that are relevant for AR content placement, rather than processing all objects and surfaces in the environment. This selective processing delivers precise AR experiences at targeted locations while minimizing overall processing time and computational load
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables the creation of tailored AR experiences that can be triggered at or proximate to specific structures or objects, enhancing user interaction and engagement through precise location tracking and visualization.
Implementation Method 1
using LIDAR technology
Data Source
AI summary
The present disclosure provides a method for creating a 3D model of a reference surface. The method includes capturing, using a capture device, a plurality of data points on the reference surface, determining a position and an orientation of the capture device related to the capture of the plurality of data points, creating a 3D data representation of the reference surface based on the plurality of data points, creating a location tracking data representation of the reference surface based the plurality of data points on the reference surface and the position and the orientation of the capture device, and creating the 3D model of the reference surface based on the 3D data representation and the location tracking data representation of the reference surface.