3D Point Cloud Characterization Using Digital Framework Morphing
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Solution Overview
Problem
Existing 3D point cloud characterization systems face inaccuracies and require costly, inconvenient hardware due to a lack of information about the point cloud, making geometrical measurements cumbersome.
Innovation Solution
A computer-implemented method for determining characteristics of an object using a 3D point cloud, involving a digital framework of a ramified 3D tree structure, morphing a 3D reference model, and identifying joints and areas of interest through machine learning algorithms and meshing techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional 3D point cloud characterization methods are used, then measurement capability is provided, but measurement precision is poor and the process is cumbersome
Solution Approach 1:
The patent introduces a digital framework as an intermediary structure between the raw 3D point cloud and the final measurement results. This framework provides a structured reference system that mediates the characterization process, enabling more accurate measurements without requiring complex specialized hardware. The digital framework acts as a bridge that transforms unstructured point cloud data into a form suitable for precise geometrical measurements.
Solution Approach 2:
The patent performs preliminary actions by constructing a digital framework and morphing a reference model onto the 3D reconstructed object before actual measurements are taken. This preliminary structuring of the data establishes a robust measurement basis that simplifies subsequent characterization tasks and significantly improves measurement precision, avoiding the need for complex real-time processing during measurement.
2Reliability
If specialized hardware equipment is used to capture 3D point cloud, then data acquisition capability is provided, but cost and convenience are reduced
Solution Approach 1:
The patent creates a digital copy (3D reconstructed object) from the captured point cloud data and performs all subsequent characterization operations on this digital replica. This copying approach allows the use of simpler, more accessible scanning hardware while maintaining high measurement reliability, as the complex processing is performed on the digital copy rather than requiring specialized hardware for each measurement operation.
Solution Approach 2:
The patent replaces complex mechanical measurement systems with a computational approach. Instead of using specialized hardware for each type of measurement, the system captures the point cloud once and then uses computational methods (digital framework construction, morphing, and automated measurement algorithms) to perform various characterization tasks, significantly improving ease of operation while maintaining reliability.
3Loss of information
If only point cloud data is used for characterization, then data processing is simplified, but information completeness is insufficient leading to inaccurate measurements
Solution Approach 1:
The patent performs preliminary actions to enrich the point cloud data by constructing a digital framework and morphing a reference model onto the 3D reconstructed object. This preliminary enrichment process adds structural information and contextual data to the raw point cloud, ensuring that subsequent measurements have access to complete information necessary for high precision without requiring additional physical measurements.
Data Source
AI summary
Methods of and systems for characterization of a 3D point cloud are disclosed. The method comprises accessing a 3D point cloud, the 3D point cloud being a set of data points representative of the object, determining, based on the 3D point cloud, a 3D reconstructed object, determining, based on the 3D reconstructed object, a digital framework of the 3D point cloud, the digital framework being a ramified 3D tree structure, the digital framework being representative of a base structure of the object, morphing a 3D reference model of the object onto the 3D reconstructed object, the morphing being based on the digital framework; and determining, based on the morphed 3D reference model and the 3D reconstructed object, characteristics of the object.