CORRESPONDENCE MATCHING IN 3D MODELS FOR 3D HAND FITTING

Maksym Tymkovych


Kharkiv National University of Radio Electronics (Ukraine)
https://orcid.org/0000-0001-5613-1104

Oleg Avrunin

oleh.avrunin@nure.ua
Kharkiv National University of Radio Electronics (Ukraine)
https://orcid.org/0000-0002-6312-687X

Karina Selivanova


Kharkiv National University of Radio Electronics (Ukraine)
https://orcid.org/0000-0003-1002-0761

Alona Kolomiiets


Vinnytsia National Technical University (Ukraine)
https://orcid.org/0000-0002-7665-6247

Taras Bednarchyk


Vinnytsia Pyrohov National Medical University (Ukraine)
https://orcid.org/0000-0003-2336-4635

Saule Smailova


D.Serikbayev East Kazakhstan State Technical University (Kazakhstan)
https://orcid.org/0000-0002-8411-3584

Abstract

Upper limb prosthetic is an area of medical research and development that aims to restore functionality and improve the quality of life of people affected by the loss of one or both upper limbs. The development and implementation of 3D scanning tools and analysis of 3D scanning data requires the use of specialized analysis methods that ensure the achievement of the required indicators. It should take into account the impact of the model resolution on the result. This paper is devoted to the analysis of finding matches between a point cloud of a hand model and another point cloud using Gromov-Wasserstein distance. For analysis, a subset of the MANO dataset was employed, containing a substantial volume of data and serving as a representative sample of the human population. The results obtained indicate the possibility of using this approach in the processing and analysis of three-dimensional data, which serves as one of the stages of designing individualized prostheses.


Keywords:

health care, medical technology, physical rehabilitation, 3D modeling, correspondence matching

Avrunin O. G. et al.: Application of 3D printing technologies in building patient-specific training systems for computing planning in rhinology. Proceedings of the International Scientific Internet Conference on Computer Graphics and Image Processing and 48th International Scientific and Practical Conference on Application of Lasers in Medicine and Biology, 2019, 1 [https://doi.org/10.1201/9780429057618-1].
  Google Scholar

Boleneus G. J. et al.: Top-down design enables flexible design of prosthetic forearms and hands. ASEE Annual Conference and Exposition, Conference Proceedings, 2019.
  Google Scholar

Cignoni P. et al.: MeshLab: an Open-Source Mesh Processing Tool. Sixth Eurographics Italian Chapter Conference, 2008, 129–136.
  Google Scholar

Garland M., Heckbert P. S.: Simplifying surfaces with color and texture using quadric error metrics. Proceedings Visualization 98, 2000.
  Google Scholar

Guidi G., Gonizzi S., Micoli L.: 3D capturing performances of low-cost range sensors for mass-market applications. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 41, 2016, 33–40 [https:// doi.org/10.5194/isprsarchives-XLI-B5-33-2016].
  Google Scholar

Kim Y. et al.: Dynamic elasticity measurement for prosthetic socket design. International Conference on Rehabilitation Robotics – ICORR, London, UK, 2017, 1281–1286 [https://doi.org/10.1109/ICORR.2017.8009425].
  Google Scholar

Neri P. et al.: Semi-automatic Point Clouds Registration for Upper Limb Anatomy. International Joint Conference on Mechanics, Design Engineering and Advanced Manufacturing – JCM, 2023, 733–742 [https://doi.org/10.1007/978-3-031-15928-2_64].
  Google Scholar

Neri P. et al.: 3D scanning of Upper Limb anatomy by a depth-camera-based system. International Journal on Interactive Design and Manufacturing, 2023 [https://10.1007/s12008-023-01248-1].
  Google Scholar

Olsen J. et al.: 3D-Printing and Upper-Limb Prosthetic Sockets: Promises and Pitfalls. IEEE Transactions on Neural Systems and Rehabilitation Engineering 29, 2021, 527–535 [https://doi.org/10.1109/tnsre.2021.3057984].
  Google Scholar

Pavlov S. V. et al.: Photoplethysmohrafic technologies of the cardiovascular control. Universum-Vinnitsa, Vinnitsa, 2007.
  Google Scholar

Pavlov S. V. et al.: A simulation model of distribution of optical radiation in biological tissues. Visnyk VNTU 3, 2011, 191–195.
  Google Scholar

Pavlov S. V. et al.: Laser photoplethysmography in integrated evaluation of collateral circulation of lower extremities. Proc. SPIE 8698, 2012, 869808.
  Google Scholar

Peyré G., Cuturi M., Solomon J.: Gromov-Wasserstein averaging of kernel and distance matrices. International Conference on Machine Learning (ICML), 2016.
  Google Scholar

Román-Casares A. M., García-Gómez O., Guerado E.: Prosthetic Limb Design and Function: Latest Innovations and Functional Results. Current Trauma Reports 4(4), 2018, 256–262 [https://doi.org/10.1007/s40719-018-0150-2].
  Google Scholar

Romero J., Tzionas D., Black M. J.: Embodied hands: Modeling and capturing hands and bodies together. ACM Transactions on Graphics 36(6), 2017, 245 [https://doi.org/10.1145/3130800.3130883].
  Google Scholar

Ryniewicz A. et al.: The use of laser scanning in the procedures replacing lower limbs with prosthesis. Measurement 112, 2017, 9–15.
  Google Scholar

Selivanova K. G. et al.: 3D visualization of human body internal structures surface during stereo-endoscopic operations using computer vision techniques. Przeglad Elektrotechniczny 9, 2021, 30–33 [https://doi.org/10.15199/48.2021.09.06].
  Google Scholar

Serkova V. et al.: Medical expert system for assessment of coronary heart disease destabilization based on the analysis of the level of soluble vascular adhesion molecules. Proc. SPIE 10445, 2017, 104453O.
  Google Scholar

Sokol Y. et al.: Using medical imaging in disaster medicine. Proceedings of IEEE 4th International Conference on Intelligent Energy and Power Systems – IEPS 2020, 287–290 [https://doi.org/10.1109/IEPS51250.2020.9263175].
  Google Scholar

Tymkovych M. et al.: Ice crystals microscopic images segmentation based on active contours. 2019 IEEE 39th International Conference on Electronics and Nanotechnology – ELNANO 2019, 493–496 [https://doi.org/10.1109/ELNANO.2019.8783332].
  Google Scholar

Tymkovych M. et al.: Detection of Chest Deviation During Breathing Using a Depth Camera. Proceedings of IEEE 8th International Conference on Problems of Infocommunications, Science and Technology – PIC S and T, 85 [https://doi.org/10.1109/PICST54195.2021.9772111].
  Google Scholar

Tymkovych M. et al.: Application of SOFA Framework for Physics-Based Simulation of Deformable Human Anatomy of Nasal Cavity. Proceedings of IFMBE, 2021, 112 [https://doi.org/10.1007/978-3-030-64610-3_14].
  Google Scholar

Tymkovych M. et al.: Application of Artificial Neural Networks for Analysis of Ice Recrystallization Process for Cryopreservation. Proceedings of IFMBE, 2021, 102 [https://doi.org/10.1007/978-3-030-64610-3_13].
  Google Scholar

Wojcik W. et al.: ECTL application for carbon monoxide measurements. Proc. of SPIE 5958, 2005, 595837.
  Google Scholar

Xu H. et al.: Gromov-wasserstein learning for graph matching and node embedding. International Conference on Machine Learning – ICML, 2019.
  Google Scholar

Zabolotna N. et al.: Diagnostic efficiency of Mueller-matrix polarization reconstruction system of the phase structure of liver tissue, Proc. SPIE 9816, 2015, 98161E [https://doi.org/10.1117/12.2229018].
  Google Scholar

Zanuttigh P. et al.: Time-of-Flight and Structured Light Depth Cameras Technology and Applications. Springer, 2016.
  Google Scholar

Download


Published
2024-03-31

Cited by

Tymkovych, M., Avrunin, O., Selivanova, K., Kolomiiets, A., Bednarchyk, T., & Smailova, S. (2024). CORRESPONDENCE MATCHING IN 3D MODELS FOR 3D HAND FITTING. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 14(1), 78–82. https://doi.org/10.35784/iapgos.5498

Authors

Maksym Tymkovych 

Kharkiv National University of Radio Electronics Ukraine
https://orcid.org/0000-0001-5613-1104

Authors

Oleg Avrunin 
oleh.avrunin@nure.ua
Kharkiv National University of Radio Electronics Ukraine
https://orcid.org/0000-0002-6312-687X

Authors

Karina Selivanova 

Kharkiv National University of Radio Electronics Ukraine
https://orcid.org/0000-0003-1002-0761

Authors

Alona Kolomiiets 

Vinnytsia National Technical University Ukraine
https://orcid.org/0000-0002-7665-6247

Authors

Taras Bednarchyk 

Vinnytsia Pyrohov National Medical University Ukraine
https://orcid.org/0000-0003-2336-4635

Authors

Saule Smailova 

D.Serikbayev East Kazakhstan State Technical University Kazakhstan
https://orcid.org/0000-0002-8411-3584

Statistics

Abstract views: 64
PDF downloads: 49


License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.


Most read articles by the same author(s)

1 2 > >>