Interior Floor Map Generation From Inter-Connected Panorama Images
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Solution Overview
Problem
Existing methods struggle to effectively generate accurate and detailed floor maps of building interiors from remote locations without physical presence, as they fail to efficiently process and integrate inter-connected images to provide comprehensive layout information.
Innovation Solution
The system employs a Floor Map Generation Manager (FMGM) to analyze inter-connected panorama images, determining relative positions and distances between viewing locations, and using metadata to generate floor maps without requiring detailed distance information from images, allowing for automated creation of floor plans and 3D models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated mapping information is generated from inter-connected images, then productivity and speed of floor map generation are improved, but device complexity and computational resource requirements increase
Solution Approach 1:
The system segments the floor map generation process into distinct modules: image acquisition, feature detection, inter-connected image matching, and floor map construction. This modular segmentation enables parallel processing of multiple images and operations, significantly improving generation speed while managing system complexity through organized functional blocks
Solution Approach 2:
The system performs preliminary feature detection and extraction from images before the actual floor map construction. By pre-processing images to identify key features, corners, and structural elements beforehand, the system reduces computational burden during the mapping phase, enabling faster overall generation without excessive complexity
2Measurement precision
If detailed distance information is required from images, then measurement precision improves, but loss of time and computational resources increase
Solution Approach 1:
The system introduces relative position relationships as an intermediary between raw image data and absolute distance measurements. By first establishing spatial relationships and geometric constraints from inter-connected images, then deriving distance information from these relationships, the system achieves acceptable measurement precision without requiring complex direct distance measurement algorithms
Solution Approach 2:
The system extracts only the essential features and geometric relationships needed for floor map generation rather than performing complete and exhaustive analysis of all image data. By focusing on key structural elements and their relative positions, the system achieves sufficient measurement precision for mapping purposes while dramatically reducing processing time and computational resources
Data Source
AI summary
Techniques are described for using computing devices to perform automated operations to generate mapping information using inter-connected images of a defined area, and for using the generated mapping information in further automated manners. In at least some situations, the defined area includes an interior of a multi-room building, and the generated information includes a floor map of the building, such as from an automated analysis of multiple panorama images or other images acquired at various viewing locations within the building—in at least some such situations, the generating is further performed without having detailed information about distances from the images' viewing locations to walls or other objects in the surrounding building. The generated floor map and other mapping-related information may be used in various manners, including for controlling navigation of devices (e.g., autonomous vehicles), for display on one or more client devices in corresponding graphical user interfaces, etc.