Textured Map Object Image Generation Using Laser Scan Data
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Solution Overview
Problem
Current systems for generating textured or pseudo 3D images of building facades using mobile mapping systems face challenges such as incorrect object identification, high computational power requirements, and the need for extensive human interaction, leading to inefficiencies in processing and increased costs.
Innovation Solution
A method that utilizes laser scan data to generate texture and lighting data, creating depth maps, normal maps, and texture maps, which are then processed to produce textured or pseudo 3D images, leveraging graphics processing units for efficient image generation and reducing the need for human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual extraction methods are used to identify texture elements in facade pictures, then identification accuracy can be maintained, but the processing speed is extremely slow (1 km/h average) and requires thousands of man hours for an average sized city
Solution Approach 1:
The patent replaces manual mechanical extraction with an automated computer vision system that uses image processing algorithms to automatically identify texture elements (windows, doors, etc.) in facade images. This substitution of manual labor with automated computational methods dramatically increases processing speed while maintaining identification accuracy through sophisticated image analysis techniques.
Solution Approach 2:
The system enables self-service by allowing the computer to automatically process and identify texture elements without human intervention. The automated pipeline includes image acquisition, automatic texture element detection, and replacement with standard elements, eliminating the need for manual extraction and reducing processing time from thousands of hours to much faster automated operations.
2Manufacturing precision
If advanced texture analysis methods are used to accurately identify texture elements, then quality of textural representation is improved, but heavy computational power is required
Solution Approach 1:
The patent segments the facade image into distinct regions corresponding to different texture elements (windows, doors, etc.) and processes each segment independently. This segmentation approach allows for targeted application of computational resources to only the necessary areas, improving textural representation quality while reducing overall computational power consumption compared to processing the entire image uniformly.
Solution Approach 2:
The system changes processing parameters by using standardized texture elements from a library instead of processing and storing complete high-resolution original images. This parameter change in the representation format reduces computational requirements while maintaining or improving textural representation quality through the use of optimized standard elements.
3Manufacturing precision
If complete original pictures with original textures are stored, then full detail and quality are preserved, but memory space requirements become excessively large
Solution Approach 1:
The patent creates simplified copies of the original facade images by replacing actual texture elements with standard texture elements from a library. These copied representations maintain the essential visual information and detail quality needed for mapping applications while occupying significantly less memory space than the complete original high-resolution pictures.
Solution Approach 2:
Instead of storing complete original images and extracting textures from them, the patent inverts the approach by storing only the essential structural information and replacing textures with standard elements. This inversion of the storage strategy reduces memory space requirements while preserving the necessary image detail quality for mapping purposes.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables the efficient generation of high-quality textured or pseudo 3D images with reduced computational burden and human interaction, significantly lowering processing time and costs, while maintaining accurate representation of building facades.
Implementation Method 1
acquiring laser scan data for the at least one map object, the laser scan data representing distances from a laser scanner to one or more points on at least one surface of the at least one map object
Data Source
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AI summary
A method of producing a textured or pseudo-3D image of one or more map objects (505) is provided comprising acquiring at least one image representing at least part of the one or more map objects (505). Laser scan data is acquired for the at least one map object, the laser scan data representing distances from a laser scanner (3(j)) to one or more points (605a-e) on at least one surface (510) of the at least one map object (505). Texture or lighting data associated with the at least one map object (505) is generated from the laser scan data, and the texture or lighting data and the image is processed in order to generate at least one textured or pseudo 3D image at least partially representing the one or more map objects (505).