Building Video Narration From Image Analysis for Indoor Navigation
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Solution Overview
Problem
Existing methods for capturing and representing building interior information, such as floor plans and textual descriptions, are often inaccurate, incomplete, and difficult to construct and maintain, making it challenging to effectively identify and navigate buildings remotely.
Innovation Solution
Automated generation of building videos with accompanying narrations using machine learning models to analyze acquired images and other building information, including panorama images, to determine building attributes and generate synchronized visual and audio descriptions, enabling efficient identification and navigation of buildings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If floor plans are used to represent building interior information, then some layout information is provided, but they are difficult to construct, maintain, scale, and visualize
Solution Approach 1:
The patent uses automated image capture and processing to create digital representations of building interiors, replacing manual floor plan creation. Images are captured using cameras or other imaging devices and processed to extract layout information, automatically generating visual representations without manual construction
Solution Approach 2:
The patent replaces manual mechanical processes of floor plan creation with automated computational image processing. Machine learning models and algorithms automatically analyze captured images to extract layout information, eliminating the need for manual drafting and maintenance of floor plans
2Loss of information
If textual descriptions of buildings are used, then some information is provided, but they are often inaccurate and incomplete
Solution Approach 1:
The patent creates accurate visual copies of building interiors through automated image capture and processing. Instead of relying on manual textual descriptions that may be inaccurate, the system captures actual images and uses computational methods to extract precise layout and attribute information directly from the visual data
Solution Approach 2:
The system uses machine learning models that can be trained and improved through feedback loops. The automated image processing and layout extraction algorithms learn from captured images and can be refined to improve accuracy, with the ability to correct and update information based on new image data
3Productivity
If automated image analysis is used to generate building videos, then building identification and navigation are improved, but computing power and time are required to process images
Solution Approach 1:
The patent divides the image processing task into segments: initial automated analysis to extract key layout information and generate basic building representations, then selective processing of specific areas or features. This segmentation allows faster initial identification while reducing overall computational load compared to processing entire high-resolution images
Solution Approach 2:
The system performs partial processing of image data by extracting only the essential layout and attribute information needed for building identification and navigation. Rather than fully processing all image details, it focuses on critical features, reducing computing power requirements while maintaining effectiveness
Data Source
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AI summary
Techniques are described for using computing devices to perform automated operations for automatically generating information about attributes of buildings from automated analysis of building information that includes floor plans and acquired building images and to subsequently using the generated building information in one or more further automated manners. In some situations, such automated generation of building information includes automatically determining objects in a building and other attributes of the building, and automatically generating descriptions about the determined building attributes. Information about such determined attributes and generated descriptions may be used in various automated manners, including for updating and/or validating information in existing building descriptions, for determining matching buildings that have similarities to indicated building descriptions or other specified criteria, for controlling device navigation (e.g., autonomous vehicles), for display on client devices in corresponding graphical user interfaces, etc.