AR Navigation Guide Generation Using Point Cloud Alignment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current Augmented Reality (AR) navigation guides require manual intervention to adjust camera angles, leading to inefficiencies and increased manual labor during point cloud recording.
Innovation Solution
A method and apparatus for generating a navigation guide using a point cloud database to determine a target navigation position, adjust the product model, and extract edge data for generating a profile diagram, which automatically aligns the camera for accurate object identification without manual modification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual intervention is used to modify the navigation guide when camera angle differs from initialization angle, then the navigation guide can be adjusted to match the actual camera position, but the process requires large amounts of manual labor and leads to slow modifications
Solution Approach 1:
The system automatically generates the navigation guide by extracting edge data from screenshots and processing it through algorithms, eliminating the need for manual intervention. The system serves itself by automatically adjusting and modifying the navigation guide based on the actual camera position and captured images, thus resolving the contradiction between precision and productivity.
Solution Approach 2:
The patent replaces manual mechanical adjustment with automated computational processing. Instead of manually modifying the navigation guide, the system uses image processing algorithms to automatically extract edge data, generate profile diagrams, and update the navigation guide, substituting human labor with automated mechanical (computational) processes.
2Productivity
If the navigation guide is generated based on initialization angle, then the process is simple and fast, but the guide cannot accurately reflect the actual camera position when angle differs
Solution Approach 1:
The system captures screenshots from the actual camera position and uses this feedback to automatically adjust the navigation guide. By processing the actual captured images and comparing them with the initialization angle data, the system generates an updated navigation guide that accurately reflects the current camera position, thus resolving the contradiction between fast generation and accurate alignment.
Solution Approach 2:
The patent dynamically changes the parameters of the navigation guide based on the actual camera angle and captured image data. Instead of using a fixed initialization angle, the system extracts edge data from screenshots and processes it to generate updated profile diagrams, thereby changing the navigation guide parameters to match the actual camera position while maintaining fast automated processing.
3Measurement precision
If edge data extraction and processing is performed on screenshot data, then the navigation guide can be automatically generated with accurate object identification, but the processing time and computational complexity increase
Solution Approach 1:
The system extracts only the essential edge data from the screenshot images, filtering out unnecessary information. By focusing on edge extraction rather than processing the entire image, the system reduces computational complexity and processing time while still achieving accurate object identification and navigation guide generation.
Solution Approach 2:
The patent applies partial processing by extracting and processing only the critical edge information from screenshots rather than performing complete image analysis. This partial action approach reduces the computational burden and processing time while maintaining sufficient precision for accurate object identification and navigation guide generation.
Data Source
AI summary
Embodiments of the disclosure provide a method and an apparatus for generating a navigation guide. In one embodiment, the method comprises: obtaining a point cloud database corresponding to an object to be identified, the object having a respective product model; determining a target navigation position based on the point cloud database; obtaining data associated with a screenshot of the product model, the screenshot captured based on the target navigation position; and generating the navigation guide for the object to be identified based on the data associated with the screenshot.