Teeth Statistic Model for Non-Invasive 3D Reconstruction
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Solution Overview
Problem
Current methods for reconstructing detailed 3D models of teeth are invasive, expensive, and fail to capture high-quality, person-specific teeth rows due to the complex appearance properties of teeth, leading to incomplete and medium-quality models.
Innovation Solution
A model-based approach using a teeth statistic model that can reconstruct a personalized 3D teeth model from a sparse set of images or a short video sequence, jointly describing shape and pose variations, and the placement of individual teeth, allowing for non-invasive reconstruction of entire teeth rows including gums from afar.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If photogrammetric camera rigs are used to capture teeth, then the capture process is non-invasive, but the reconstruction quality is poor due to complex appearance properties of teeth
Solution Approach 1:
The patent introduces a teeth statistic model as an intermediary that bridges the gap between 2D image data and 3D teeth reconstruction. This statistical model, trained on high-quality 3D dental scans, serves as a mediator that translates appearance properties from images into accurate 3D geometry, resolving the contradiction between non-invasive capture and reconstruction quality.
Solution Approach 2:
The patent changes the approach from direct photogrammetric reconstruction to a parameter-based statistical model. By representing teeth through statistical parameters (shape, pose, placement variations) rather than direct geometric measurement, the system achieves high-quality reconstruction from standard photographs without requiring specialized equipment.
2Measurement precision
If shape-from-shading methods are used to exploit reflectance properties, then some teeth information can be captured, but the models are incomplete and medium-quality due to occlusions
Solution Approach 1:
The patent segments the teeth row into individual teeth, each represented by its own statistical model. This segmentation allows the system to handle occlusions locally - when one tooth is occluded, only that specific tooth's parameters need to be inferred, while other visible teeth provide constraints through the statistical model, resulting in complete 3D reconstructions.
Solution Approach 2:
The statistical model provides feedback by using visible teeth to constrain and guide the reconstruction of occluded teeth. The model iteratively refines the complete teeth row configuration based on observed appearance properties, ensuring that even occluded regions are accurately reconstructed through the statistical prior.
3Manufacturing precision
If intra-oral scanners are used to capture teeth at high quality, then detailed 3D models can be obtained, but the procedure is invasive, expensive, and time-consuming
Solution Approach 1:
The patent creates a statistical copy of high-quality 3D teeth models from a database trained on professional scans. Instead of using expensive intra-oral scanners, the system copies the essential geometric information from the statistical model, which encapsulates the high-quality reconstruction results without requiring the complex scanning hardware.
Solution Approach 2:
The patent replaces the mechanical intra-oral scanning system with a computational statistical model approach. The physical scanning process is substituted by a software-based statistical reconstruction system that uses standard photographs and learned parameters to generate high-quality 3D models, eliminating the need for expensive hardware.
4Reliability
If non-person specific teeth row models are used to reconstruct teeth, then plausible re-rendering results can be achieved, but the true person-specific mouth appearance is not reproduced
Solution Approach 1:
The patent applies local quality by creating individual tooth statistical models that capture person-specific variations in shape, pose, and placement. Each tooth is modeled with its own statistical parameters, allowing the system to reproduce the unique appearance characteristics of each individual's teeth while maintaining overall anatomical plausibility through the statistical prior.
Data Source
AI summary
A system and method for non-invasive reconstruction of an entire object-specific or person-specific teeth row from just a set of photographs of the mouth region of an object (e.g., an animal) or a person (e.g., an actor or a patient) are provided. A teeth statistic model defining individual teeth in a teeth row can be developed. The teeth statistical model can jointly describe shape and pose variations per tooth, and as well as placement of the individual teeth in the teeth row. In some embodiments, the teeth statistic model can be trained using teeth information from 3D scan data of different sample subjects. The 3D scan data can be used to establish a database of teeth of various shapes and poses. Geometry information regarding the individual teeth can be extracted from the 3D scan data. The teeth statistic model can be trained using the geometry information regarding the individual teeth.