Template-Based 3D Object Reconstruction from Point Clouds
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Solution Overview
Problem
Existing methods for generating 3D representations of objects require specialized, cumbersome, and costly hardware equipment, such as 3D laser scanners, and there is a need for cost-effective systems and methods to achieve efficient 3D representation from 3D point clouds.
Innovation Solution
Utilizing non-specialized hardware like mobile devices with cameras, combined with 3D model templates, to align, scale, and apply local deformations to 3D point cloud reconstructions, generating accurate 3D representations through processes like denoising, alignment, and deformation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If specialized hardware equipment such as 3D laser scanners is used, then measurement precision and reliability of 3D data acquisition is improved, but device complexity and cost increase
Solution Approach 1:
The patent uses 2D images captured by standard cameras as copies or projections of the 3D object, which are then processed to reconstruct the 3D model. This avoids the need for expensive 3D scanning hardware while achieving comparable results through computational methods.
Solution Approach 2:
The patent replaces mechanical 3D scanning systems with a computational approach using 2D image processing. Instead of using specialized optical-mechanical scanning equipment, the system uses standard cameras combined with algorithmic processing to achieve 3D reconstruction.
2Manufacturing precision
If specialized 3D scanning equipment is used, then manufacturing precision of 3D representations is improved, but ease of manufacture and accessibility deteriorates
Solution Approach 1:
The patent makes the 3D reconstruction system universal by using standard cameras that are already present in most mobile devices. This multi-functional approach allows the same hardware to serve both general photography purposes and specialized 3D scanning functions, greatly improving accessibility.
Solution Approach 2:
The patent employs inexpensive standard camera sensors and processors that are mass-produced and readily available, replacing expensive specialized scanning equipment. This approach prioritizes accessibility and cost-effectiveness while maintaining adequate precision for many applications.
3Manufacturing precision
If complex processing algorithms are applied to 3D point clouds, then manufacturing precision is improved, but productivity and processing time deteriorates
Solution Approach 1:
The patent applies preliminary processing steps such as denoising and point cloud completion before the main reconstruction algorithms. By preparing the data in advance with simpler operations, the subsequent complex processing requires fewer iterations and converges faster, improving overall productivity.
Data Source
AI summary
The disclosed systems, structures, and methods are directed to generating a three-dimensional (3D) representation of an object, the method comprising accessing a 3D point cloud reconstruction of the object, accessing a 3D model template, the 3D model template defining a generic version of the object, aligning, in a geometrical space, the 3D model template with respect to the 3D point cloud reconstruction, adjusting a scale of the 3D model template, and applying local deformations to a surface of the 3D model template.