Automatic Indoor Navigation via Unordered Spherical Panorama Sequencing
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Solution Overview
Problem
Existing navigation technologies fail to provide effective indoor navigation and exploration tools, as panoramic images of indoor spaces require manual sequencing and often rely on expensive external positioning systems for accurate navigation.
Innovation Solution
A method and system for automatic pose estimation that receives uncalibrated and unordered panoramic images, extracts feature points, generates a match matrix, constructs a minimal spanning tree, and identifies navigation paths between images, allowing for automatic sequencing and navigation within indoor spaces without external positioning systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual sequencing is used to associate panoramic images, then navigation assistance is provided, but the process requires significant human effort and time
Solution Approach 1:
The system automatically sequences panoramic images by extracting features, generating match matrices, constructing minimal spanning trees, and estimating poses without human intervention. The algorithm self-organizes the unordered image collection into a navigable sequence based on visual content analysis.
Solution Approach 2:
The manual mechanical process of sequencing images is replaced with an automated computational system that uses feature extraction, match matrix generation, and minimal spanning tree construction to determine image sequences automatically.
2Measurement precision
If external positioning systems are used for accurate navigation, then navigation precision is improved, but the cost and complexity of the system increases
Solution Approach 1:
Instead of using expensive external positioning systems, the patent creates a virtual copy of the physical space through panoramic images. The system reconstructs the spatial relationships and navigation paths by analyzing visual features in the images, providing an affordable alternative to GPS-based systems.
Solution Approach 2:
External positioning systems (mechanical/electronic hardware) are replaced with a software-based visual analysis system that uses feature extraction, match matrices, and pose estimation algorithms to achieve navigation accuracy without physical positioning hardware.
3Productivity
If automated pose estimation is implemented, then sequencing efficiency is improved, but computational complexity increases
Solution Approach 1:
The complex automated sequencing task is divided into manageable segments: feature extraction from individual images, generation of match matrices between image pairs, construction of minimal spanning trees to organize relationships, and pose estimation for each image triplet. This modular approach improves efficiency while managing computational complexity.
Data Source
AI summary
Methods and systems for automatically generating pose estimates from uncalibrated unordered panoramas are provided. An exemplary method of automatically generating pose estimates includes receiving a plurality of uncalibrated and unordered panoramic images that include at least one interior building image, and extracting, for each panoramic image, feature points. The method includes generating a match matrix for all the panoramic images based on the one or more feature points, constructing a minimal spanning tree based on the match matrix, identifying a first and second panoramic image, based on the minimal spanning tree, wherein the second panoramic image is associated with the first panoramic image providing a navigation from the first panoramic image to the second panoramic image.