3D Point Cloud Compression with Scan Line Reconstruction
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Solution Overview
Problem
Existing 3D laser scanning systems generate excessive data due to varying vehicle speeds and GPS time inconsistencies, leading to inefficient data storage and reduced model accuracy when thinning out point groups.
Innovation Solution
A data compression device and method that thins out 3D point group data based on arbitrary criteria, such as vehicle speed and outdoor structure type, while maintaining the ability to recreate accurate 3D models by preserving necessary point groups and calculating pseudo scan lines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If point groups are thinned out to reduce data storage requirements, then data storage efficiency is improved, but 3D model accuracy deteriorates
Solution Approach 1:
The patent applies local quality by differentiating thinning strategies based on vehicle speed conditions. When the vehicle is moving, point groups are thinned out more aggressively. When the vehicle is stopped or moving very slowly, point groups are preserved to maintain model accuracy. This localized approach to data retention ensures storage efficiency without sacrificing critical measurement quality.
Solution Approach 2:
The patent changes the parameter of point group retention based on vehicle speed conditions. By monitoring GPS speed data, the system dynamically adjusts whether to delete or retain point groups, transforming a static data retention approach into a dynamic one that adapts to operational conditions, thereby resolving the contradiction between storage efficiency and model accuracy.
2Manufacturing precision
If all point groups are retained to ensure model accuracy, then 3D model accuracy is maintained, but data storage requirements increase enormously
Solution Approach 1:
The patent extracts and removes redundant point groups from the dataset based on vehicle speed criteria. By identifying and deleting point groups acquired when the vehicle is moving (where redundancy is higher), the system significantly reduces data storage requirements while preserving essential point groups needed for accurate 3D modeling.
Solution Approach 2:
Instead of retaining all point groups (excessive action), the patent applies partial action by selectively keeping only the necessary point groups for model accuracy. This partial retention strategy, guided by vehicle speed conditions, achieves the minimum necessary data storage while maintaining sufficient model quality.
3Quantity of substance
If point groups are deleted without tracking GPS time, then data storage efficiency is improved, but the ability to recreate accurate 3D models deteriorates due to lost temporal information
Solution Approach 1:
The patent performs preliminary action by recording the GPS time of deleted point groups before actual deletion occurs. This advance documentation of temporal information allows the system to later reconstruct scan lines accurately by referencing the stored GPS timestamps, preventing information loss despite data deletion.
Solution Approach 2:
The patent creates a copy of the GPS time information for deleted point groups. Instead of deleting the temporal data along with the point groups, the system copies the GPS timestamp to a separate storage structure, enabling reconstruction of scan line relationships without retaining the full point group data.
Data Source
AI summary
An object of the present invention is to provide a data compression device, a data compression method, and a program capable of thinning out a point group acquired by a three-dimensional (3D) laser scanner without affecting the creation of a 3D model. A data compression device according to the present invention is a data compression device which compresses 3D point group data indicating 3D coordinates of points on a surface of an outdoor structure acquired using a 3D laser scanner while moving including: a point group deleting part which thins out the 3D point group data according to an arbitrary criterion and calculates scan lines deleted through the thinning-out of the 3D point group data; and an extraction processing part which creates a 3D model from the thinned 3D point group data while skipping the deleted scan lines which are stored.