AR Tracking Using Simplified 2D Façade Models
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Solution Overview
Problem
Augmented reality systems face challenges in maintaining accurate tracking between real and virtual objects, leading to jitter or unnatural placement of virtual items due to processor-intensive calculations required for complex 3D point cloud models, especially on resource-limited mobile devices.
Innovation Solution
The use of compressed or simplified 3D point cloud models and two-dimensional façade data, combined with initial rough location estimates from GPS or other location-based systems, to efficiently match and track virtual objects within an augmented reality environment, reducing processing demands and improving real-time performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex 3D point cloud models are used for tracking, then tracking accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The patent segments the complex 3D point cloud model into multiple simplified 2D façade components representing different building surfaces. Each façade is processed independently for feature detection and matching, reducing the computational burden of processing the entire 3D model as a single complex structure while maintaining tracking accuracy through cumulative façade matching.
Solution Approach 2:
The patent creates simplified 2D copies of 3D façade surfaces from the original complex 3D point cloud model. These 2D façade representations serve as computationally efficient substitutes that retain the essential geometric and visual characteristics needed for accurate tracking and matching, enabling real-time processing on mobile devices.
2Measurement precision
If complex 3D point cloud models are used for tracking, then tracking accuracy is improved, but device resource requirements increase
Solution Approach 1:
The patent divides the complex 3D point cloud into multiple simpler 2D façade segments, each representing a portion of a building surface. This segmentation allows mobile devices with limited processing power to handle each façade independently, reducing the overall computational complexity while preserving the accuracy needed for precise virtual object placement.
Solution Approach 2:
The patent uses lightweight 2D façade representations as simplified proxies for the heavy 3D point cloud data. These 2D models require significantly fewer computational resources to process and can be quickly generated and discarded, enabling resource-constrained mobile devices to perform accurate augmented reality tracking without needing powerful hardware.
3Loss of time
If GPS location estimates are used, then processing time is reduced, but location precision decreases
Solution Approach 1:
The patent uses GPS to obtain a preliminary rough location estimate before performing detailed image-based façade matching. This preliminary positioning narrows down the search area for subsequent processing, allowing the system to quickly identify relevant building façades in the vicinity and perform detailed matching only on those candidates, thereby reducing overall processing time while maintaining accuracy through the two-stage approach.
Data Source
AI summary
Systems and methods for image based location estimation are described. In one example embodiment, a first positioning system is used to generate a first position estimate. Point cloud data describing an environment is then accessed. A two-dimensional surface of an image of an environment is captured, and a portion of the image is matched to a portion of key points in the point cloud data. An augmented reality object is then aligned within one or more images of the environment based on the match of the point cloud with the image. In some embodiments, building façade data may additionally be used to determine a device location and place the augmented reality object within an image.