A Fast Geometric Deformation Method to Adapt a Foot to a Platform

  • J. M. Buades
  • M. González-Hidalgo
  • Francisco J. Perales
  • S. Ramis-Guarinos
  • A. Oliver
  • E. Montiel
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 7)


The main goal of this research work is to develop a new system that designs shoes that adapts exactly to the foot shape. This research is based on a biomechanical anatomical structure of the foot and of the deformable shape. The system automatically selects significant foot points. We consider several anthropometrical parts of the foot in order to apply a global deformation with different axis. Also an interpolation process is designed to combine the several parts of the foot in an efficient and accurate manner. We consider different criteria in the deformation process because the top is rigid and the sole is assumed non-rigid. The system is implemented in an optimized software version in order to control the computational cost of the deformation process. A prototype of oriented commercial Application Programming Interface (API) is developed for non specialized users of the system. The results presented evaluate the error between deformations and we validate the error of several users (foot and last). Also the low error obtained guarantees the comfort of the foot that is a very important objective in this area of research.


Boundary Element Method Axis Translation Laplacian Smoothing Deformation Line Metatarsal Joint 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work is subsidized by the national project DPI2009-14738-C02-01 of the MICIIN Spanish Government coordinated by INESCOP (Asoc. investigacin industrias del calzado y conexas) and developed in collaboration with UIB (University of Balearic Islands).


  1. 1.
    Arampatzis A, Brggemann GP, Klapsing GM (2002) A three-dimensional shank-foot model to determine the foot motion during landings. Med Sci Sports Exerc 34(1):130–138CrossRefGoogle Scholar
  2. 2.
    Carson MC, Harrington ME, Thompson N, O’Connor JJ, Theologis TN (2001) Kinematic analysis of a multi-segment foot model for research and clinical applications: a repeatability analysis. J Biomech 34(10):1299–1307CrossRefGoogle Scholar
  3. 3.
    Cheng FT, Peng DB (1999) A systematic approach for developing a foot size information system for shoe last design. Int J Ind Ergonomics 25(2):171–185. doi: 10.1016/S0169-8141(98)00098-5 MathSciNetCrossRefGoogle Scholar
  4. 4.
    Desbrun M, Meyer M, Schröder P, Barr AH (1999) Implicit fairing of irregular meshes using diffusion and curvature flow. In: Proceedings of the 26th annual conference on computer graphics and interactive techniques, SIGGRAPH’99, pp 317–324. ACM Press/Addison-Wesley Publishing Co, New York. doi: 10.1145/311535.311576
  5. 5.
    Houston VL, Luo G, Mason CP, Mussman M, Garbarini M, Beattie AC (2006) Changes in male foot shape and size with weightbearing. J Am Podiatr Med Assoc 96(4):330–343Google Scholar
  6. 6.
    Kavan L, Zara J (2003) Real-time skin deformation with bones blending. In: WSCG short papers proceedingsGoogle Scholar
  7. 7.
    Kim SY, Lee K, Hwang T (2002) A grouping algorithm for custom-tailored products. J Mater Process Technol 130–131:618–625CrossRefGoogle Scholar
  8. 8.
    Kos L, Duhovnik J (2002) A system for footwear fitting analysis. In: Proceedings of the international design conference design, pp 1187–1192Google Scholar
  9. 9.
    Leng J, Du R (2005) A deformation method for shoe last customization. Comput Aided Des Appl 2(1–4):11–18Google Scholar
  10. 10.
    Li G, Joneja A (2004) A morphing-based surface blending operator for footwear CAD. In: ASME-IMECE conference proceedings, pp 269–273. doi: 10.1115/IMECE2004-60719
  11. 11.
    Lowe J (1927) Method and means for visually determining the fit of footwear. U.S. Pantent Publication. Washington DC. Publication No. US 1614988 A. Application No. US 275310 AGoogle Scholar
  12. 12.
    Luximon A, Goonetilleke RS (2004) Foot shape modeling. Hum Factors 46(2):304–315CrossRefGoogle Scholar
  13. 13.
    Luximon A, Goonetilleke RR, Tsui KL (2003) Foot landmarking for footwear customization. Ergonomics 46(4):364–383CrossRefGoogle Scholar
  14. 14.
    Luximon A, Goonetilleke RR, Tsui KL (2003) Footwear fit categorization. In: Tseng M, Piller F (eds) The customer centric enterprise: advances in mass customization and personalization, chap. 28. Springer, Heidelberg, pp 491–499Google Scholar
  15. 15.
    Luximon A, Goonetilleke RS, Tsui KL (2005) Foot landmarking for footwear customization. Comput Aided Des Appl 2(1):11–18Google Scholar
  16. 16.
    Luximon A, Goonetilleke R, Zhang M (2005) 3D foot shape generation from 2D information. Ergonomics 48(6):625–641CrossRefGoogle Scholar
  17. 17.
    Mochimaru M, Kouchi M, Dohi M (2000) Analysis of 3-D human foot forms using the free form deformation method and its application in grading shoe lasts. Ergonomics 43(9):1301–1313CrossRefGoogle Scholar
  18. 18.
    Rout N, Zhang YF, Khandual A, Luximon A (2010) 3D foot scan to custom shoe last. Int J Comput Commun Technol 1(2–3-4):14–18. Special Issue International Conference [ACCTA-2010]Google Scholar
  19. 19.
    Rupérez MJ (2011) Multidisciplinary techniques for the simulation of the contact between the foot and the shoe upper in gait: virtual reality, computational biomechanics, and artificial neural networks. Ph.D. thesis, Departamento de Ingienería Mecánica y Materiales, Universidad de ValenciaGoogle Scholar
  20. 20.
    Rupérez MJ, Monserrat C, Alcañiz M (2008) Simulation of the deformation of materials in shoe uppers in gait. Force distribution using finite elements. Int J Interact Des Manuf 2:59–68CrossRefGoogle Scholar
  21. 21.
    Rupérez MJ, Monserrat C, Alemany S, Juan M, Alcañiz M (2010) Contact model, fit process and, foot animation for the virtual simulator of the footwear comfort. Comput Aided Des 42(5):425–431CrossRefGoogle Scholar
  22. 22.
    Tang Y, Hui K (2007) The effect of tendons on foot skin deformation. Comput Aided Des 39(7):583–597. doi: 10.1016/j.cad.2007.01.013 CrossRefGoogle Scholar
  23. 23.
    Tang Y, Hui K (2011) Human foot modeling towards footwear design. Comput Aided Des 43(12):1841–1848. doi: 10.1016/j.cad.2011.08.005 CrossRefGoogle Scholar
  24. 24.
    Taubin G (1995) A signal processing approach to fair surface design. In: Proceedings of the 22nd annual conference on computer graphics and interactive techniques, SIGGRAPH ’95, pp 351–358. ACM, New York. doi: 10.1145/218380.218473
  25. 25.
    Telfer S, Woodburn J (2010) The use of 3D surface scanning for the measurement and assessment of the human foot. J Foot Ankle Res 3:19CrossRefGoogle Scholar
  26. 26.
    Wang CS (2010) An analysis and evaluation of fitness for shoe lasts and human feet. Comput Ind 61(6):532–540. doi: 10.1016/j.compind.2010.03.003 CrossRefGoogle Scholar
  27. 27.
    Witana CP, Goonetilleke RS, Xiong S, Au EY (2009) Effects of surface characteristics on the plantar shape of feet and subjects perceived sensations. Appl Ergonomics 40(2):267–279. doi: 10.1016/j.apergo.2008.04.014 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • J. M. Buades
    • 1
  • M. González-Hidalgo
    • 1
  • Francisco J. Perales
    • 1
  • S. Ramis-Guarinos
    • 1
  • A. Oliver
    • 1
  • E. Montiel
    • 2
  1. 1.Computer Graphics, Vision and Artificial Intelligence Group, Department of Mathematics and Computer ScienceUniversity of Balearic IslandPalma de MallorcaSpain
  2. 2.INESCOP, Footwear Technological InstituteElda-AlicanteSpain

Personalised recommendations