Automated Shoe Metrology by X-Ray Computed Tomography - 23.48
M. Leipert et al., "Automated Shoe Metrology by X-Ray Computed Tomography", Proc. of 3DBODY.TECH 2023 - 14th Int. Conf. and Exh. on 3D Body Scanning and Processing Technologies, Lugano, Switzerland, 17-18 Oct. 2023, #48, https://doi.org/10.15221/23.48.
Title:
Automated Shoe Metrology by X-Ray Computed Tomography
Authors:
Martin LEIPERT 1,2, Gabriel HERL 1, Michael MUELLER 3, Joshua MESSKEMPER 3, Simon ZABLER 1
1 Deggendorf Institute of Technology, Deggendorf, Germany;
2 Pattern Recognition Lab, Friedrich-Alexander-Universitaet Erlangen-Nuernberg (FAU), Erlangen, Germany;
3 OneFID GmbH, Cologne, Germany
Abstract:
Automation of shoe metrology is crucial to providing fit information for shoes on a large scale. Here, we examine a segmentation technique to extract the inner shoe volume (ISV) from Computed Tomography (CT) data - the proposed approach leverages artificial neural networks to extract shoe parts for automated metrology precisely. The neural network architecture is customized to facilitate the extraction of ISV by integrating spatial attention mechanisms. Furthermore, a neural network segmentation algorithm removes filler materials virtually. This process yields enhancements of 1.3% in F1-score through material removal and an additional 1.4% through the incorporation of spatial attention. Notably, spatial attention mechanisms yield improved outcomes at the aperture of the shoe. The elimination of filler materials reduces false positive segmentations. The segmentation outcomes are utilized to generate surface meshes. These are compared to surface meshes derived from annotated data. We measure an average Hausdorff distance between annotated and labelled data of 2.1 mm. The discrepancy is primarily attributed to deformations and artifacts. On both sets, we measure the effective shoe length. Precision and accuracy metrics for the extracted measurement from ANN-segmented data attain 0.8 mm and 1.8 mm, respectively. For meshes obtained from label data, the precision is 0.2 mm, and the accuracy is 2.5 mm. Our findings underscore the accuracy of the extracted shoe interior volumes, rendering them suitable for metrological applications. Limitations include unsolved issues with separation reliability and deformation.
Keywords:
Automated Shoe Fitting, Shoe Metrology, Computed Tomography
Full paper:
Presentation:
Details:
Proceedings: 3DBODY.TECH 2023, 17-18 Oct. 2023, Lugano, Switzerland
Paper id#: 48
DOI: 10.15221/23.48
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