3D Scan Data Extraction via Voxel Polyhedron Segmentation
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Solution Overview
Problem
Large three-dimensional scan data sets from physical environments are computationally intensive and require significant resources to process, making it challenging to visualize and manipulate them interactively, especially when only a localized subset of the data is needed for manipulation.
Innovation Solution
The method involves defining an extraction polyhedron within the three-dimensional visual representation of a physical space to selectively extract and store data points or polygons, allowing for efficient data manipulation by bisecting polygons and testing points to determine if they are inside or outside the polyhedron, thereby reducing computational load and resource requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the entire large three-dimensional scan data set is processed for visualization and manipulation, then complete spatial representation is achieved, but computational resources and processing time increase significantly
Solution Approach 1:
The patent divides the large three-dimensional scan data set into multiple smaller subsets using a voxel-based structure. Each voxel contains only the data points that fall within its three-dimensional bounds, allowing the system to process and visualize only the relevant portions of the data set at any given time, thereby reducing computational load while maintaining complete spatial representation capability.
Solution Approach 2:
The patent extracts only the necessary data points from the complete scan data set by using a queryable voxel structure. When a user defines a region of interest (such as a bounding box or sphere), the system extracts only the data points contained within that region, avoiding the need to process the entire large data set and significantly reducing processing time.
2Loss of information
If all data points from the three-dimensional scan are retained for potential manipulation, then data completeness is maintained, but memory space and computational resources increase
Solution Approach 1:
The patent segments the complete data set into a three-dimensional grid of voxels, where each voxel stores only the data points within its spatial bounds. This segmentation allows the system to maintain data completeness by preserving all original data points in the voxel structure, while reducing memory usage by organizing data in a compact, spatially-efficient manner that avoids redundant storage.
Solution Approach 2:
The patent implements a hierarchical voxel structure where voxels can be nested at different levels of detail. Coarse voxels contain aggregated information about larger regions, while finer voxels contain detailed data points. This nested structure allows the system to maintain complete data at the finest level while enabling efficient querying and manipulation at coarser levels, reducing overall memory requirements.
3Productivity
If complex data structures are used to organize the three-dimensional scan data, then data organization and query efficiency are improved, but device complexity increases
Solution Approach 1:
The patent uses a simple three-dimensional grid-based voxel structure to organize data, avoiding complex hierarchical or graph-based data structures. Each voxel is defined by basic three-dimensional coordinates and contains an array of data points, providing an intuitive and easily implementable organization scheme that improves query efficiency through spatial locality while maintaining low structural complexity.
Data Source
AI summary
Methods and systems for extracting data from a three-dimensional visual representation of a physical space, the three-dimensional visual representation of the physical space comprising either a mesh of a plurality of polygons or point cloud data points. The present method includes the steps of defining an extraction polyhedron enclosed by a boundary surface, identifying data inside the boundary surface of the extraction polyhedron for extraction, extracting the data identified inside the boundary surface of the extracting polyhedron and storing the extracted data in data storage.