Batch Extraction of Human Anatomical Feature Parameters
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Solution Overview
Problem
Conventional methods for obtaining human anatomical feature parameters are labor-intensive and time-consuming, as they involve measuring individual samples sequentially, which hampers efficiency in data-driven research and development.
Innovation Solution
A method and apparatus for batch extraction of human anatomical feature parameters, involving the generation of an average model from multiple samples, calculation of point correspondences, and measurement of samples on the average model to output feature parameter data in batch.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional single-sample measurement method is used, then measurement accuracy is maintained, but time consumption and labor intensity increase significantly
Solution Approach 1:
The patent applies preliminary action by pre-aligning all sample point clouds to a reference coordinate system and pre-establishing the geometric model before batch measurement. This preparation work is performed once, enabling subsequent rapid measurement of multiple samples without repeated alignment operations, thus resolving the time consumption issue while maintaining measurement accuracy
Solution Approach 2:
The patent merges multiple sample measurements into a unified batch processing framework. By combining multiple sample point clouds and performing simultaneous parameter extraction on the geometric model, the system achieves efficient batch measurement that improves productivity while controlling time loss through optimized computational workflows
2Productivity
If batch measurement method is implemented, then time cost is reduced, but measurement precision may be compromised
Solution Approach 1:
The patent applies local quality by performing measurements at specific key locations on the geometric model rather than uniformly across the entire surface. By focusing measurement efforts on critical feature points and regions, the system maintains high measurement precision for essential parameters while enabling efficient batch processing of multiple samples
Solution Approach 2:
The patent uses copying by creating a reference geometric model from sample data and using this model as a template for batch measurement. The measured parameters are then copied and applied to evaluate multiple samples against this standardized model, ensuring consistent and precise parameter extraction across all samples while maintaining high productivity
3Measurement precision
If complex alignment and transformation calculations are performed, then measurement accuracy is improved, but calculation time increases
Solution Approach 1:
The patent applies preliminary action by performing all complex alignment and affine transformation calculations once during the model setup phase. The reference coordinate system and transformation matrices are pre-computed, eliminating the need for repeated complex calculations during batch measurement, thus maintaining spatial correspondence accuracy while significantly reducing calculation time
Solution Approach 2:
The patent applies dynamics by using efficient computational algorithms that adapt the calculation complexity to the specific measurement needs. The system dynamically selects appropriate calculation methods based on the geometric model characteristics and measurement requirements, optimizing the balance between measurement precision and calculation time for batch processing
Data Source
AI summary
Provided are a method and an apparatus for implementing batch extraction of human anatomical feature parameters. The method includes: obtaining a to-be-measured sample; generating an average model; calculating a point correspondence of a spatial location formed by the average model and each to-be-measured sample; measuring each to-be-measured sample on the average model; and outputting feature parameter data of each to-be-measured sample in batch. Calculation time is reduced by combining feature point extraction with affine transformation, and corresponding points are calculated through a non-rigid registration method to achieve batch and quick measurement.