body2vec: 3D Point Cloud Reconstruction for Precise Anthropometry with Handheld Devices
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data Collection
2.2. Segmentation Model
2.3. 3D Reconstruction and Measurement
3. Results
3.1. Mask Segmentation
3.2. Segmented Point Cloud Evaluation
3.3. Abdominal Perimeter Measurements
4. Discussion and Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Abbreviations
LiDAR | Light Detection and Ranging o Laser Imaging Detection and Ranging |
SfM | Structure from motion |
References
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Measure | Mean | Standard Deviation | Min | Max | ||||
---|---|---|---|---|---|---|---|---|
BRemNet | Mask R-CNN | BRemNet | Mask R-CNN | BRemNet | Mask R-CNN | BRemNet | Mask R-CNN | |
Hamming loss | 0.04149 | 0.04734 | 0.00559 | 0.00693 | 0.03428 | 0.03889 | 0.05578 | 0.06111 |
Jaccard | 0.86457 | 0.84577 | 0.01913 | 0.02830 | 0.83373 | 0.80468 | 0.90798 | 0.89994 |
F-measure | 0.92726 | 0.91620 | 0.01096 | 0.01655 | 0.90933 | 0.89177 | 0.95177 | 0.94733 |
Accuracy | 0.95851 | 0.95266 | 0.00559 | 0.00693 | 0.94422 | 0.93889 | 0.96572 | 0.96111 |
FPR | 0.02929 | 0.03226 | 0.04308 | 0.04979 | 0.03844 | 0.03938 | 0.03918 | 0.04252 |
FNR | 0.07050 | 0.08385 | 0.09068 | 0.11291 | 0.05415 | 0.06017 | 0.06929 | 0.08992 |
Video 1 | Video 2 | Video 3 | Video 4 | Video 5 | Video 6 | Video 7 | Video 8 | Video 9 | Video 10 | |
---|---|---|---|---|---|---|---|---|---|---|
min Jaccard | 0.6000 | 0.6606 | 0.7035 | 0.5057 | 0.5942 | 0.5967 | 0.3723 | 0.6195 | 0.4757 | 0.4541 |
Jaccard < 0.8 | 25.57% | 11.11% | 3.23% | 29.73% | 12.24% | 30.43% | 21.43% | 21.16% | 34.56% | 38.57% |
max FN | 110,746 | 67,498 | 77,635 | 96,063 | 254,296 | 59,932 | 152,988 | 59,032 | 87,076 | 84,309 |
Measure | Mean | Standard Deviation | Min | Max | ||||
---|---|---|---|---|---|---|---|---|
BRemNet | Mask R-CNN | BRemNet | Mask R-CNN | BRemNet | Mask R-CNN | BRemNet | Mask R-CNN | |
Jaccard | 0.73543 | 0.28999 | 0.11578 | 0.13299 | 0.51644 | 0.06965 | 0.84800 | 0.45189 |
F-measure | 0.84264 | 0.43349 | 0.08188 | 0.17417 | 0.68112 | 0.13023 | 0.91775 | 0.62249 |
FPR | 0.15062 | 0.50837 | 0.17849 | 0.50000 | 0.10318 | 0.56022 | 0.13559 | 0.51065 |
FNR | 0.15077 | 0.63428 | 0.17222 | 0.74144 | 0.09727 | 0.74409 | 0.13376 | 0.73075 |
Mean Error (cm) | Standard Deviation (cm) | |||
---|---|---|---|---|
Hip | Waist | Hip | Waist | |
LiDAR-based meshes | 7.935 | 0.910 | 6.864 | 1.808 |
Unsegmented point clouds. | 271.708 | 302.718 | 87.375 | 123.548 |
BRemNet-segmented point clouds | 6.701 | 4.128 | 4.419 | 3.148 |
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Trujillo-Jiménez, M.A.; Navarro, P.; Pazos, B.; Morales, L.; Ramallo, V.; Paschetta, C.; De Azevedo, S.; Ruderman, A.; Pérez, O.; Delrieux, C.; et al. body2vec: 3D Point Cloud Reconstruction for Precise Anthropometry with Handheld Devices. J. Imaging 2020, 6, 94. https://doi.org/10.3390/jimaging6090094
Trujillo-Jiménez MA, Navarro P, Pazos B, Morales L, Ramallo V, Paschetta C, De Azevedo S, Ruderman A, Pérez O, Delrieux C, et al. body2vec: 3D Point Cloud Reconstruction for Precise Anthropometry with Handheld Devices. Journal of Imaging. 2020; 6(9):94. https://doi.org/10.3390/jimaging6090094
Chicago/Turabian StyleTrujillo-Jiménez, Magda Alexandra, Pablo Navarro, Bruno Pazos, Leonardo Morales, Virginia Ramallo, Carolina Paschetta, Soledad De Azevedo, Anahí Ruderman, Orlando Pérez, Claudio Delrieux, and et al. 2020. "body2vec: 3D Point Cloud Reconstruction for Precise Anthropometry with Handheld Devices" Journal of Imaging 6, no. 9: 94. https://doi.org/10.3390/jimaging6090094