Estimation to Use the Stick Figure of Kinect® Version 2 for Digital Anthropometry

  • Sabine WenzelEmail author
  • Juliana Buchwald
  • Hartmut Witte
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 826)


In this paper we examine the possibility to use the integrated stick figure and their joint positions of Microsoft® Kinect® version 2 for digital measurement of human body dimensions. Manual anthropometric measurement data and the indirect parameter calculation based on Kinect® joints were compared for selected human body dimensions. This paper takes a closer look at the length measurements of body height and arm span.

15 female participants took part in a subject test. Participants stood frontal to the Kinect® in two different stages (feet together and slightly apart; both with and without shoes) and in three different poses. Each parameter was analysed by three different algorithms based on the Kinect® joint data.

For determination of body height, the indirect parameter calculation seems to be a possible replacement of the direct manual anthropometric measurement, if the accuracy claim is low. We observed deviations between the values derived from Kinect® data and the direct anthropometric values up to 5 cm. Arm span data as well shows linear trends, but deviations are higher. Multivariate analyses seem to be necessary.


Digital anthropometry Stick figure Microsoft® Kinect® 


  1. Annichini M, Arena R, Fanini M, Fattorel M, Pavei D, Tasson D, Garro V, Lovato C, Giachetti A (2013) Shape processing for digital anthropometry. In: Eurographics WorkshopGoogle Scholar
  2. Aslam M, Rajbdad F, Khattak S, Azmat S (2017) Automatic measurement of anthropometric dimensions using frontal and lateral silhouettes. IET Comput Vis 11(6, 9):434–447Google Scholar
  3. Chiu C-Y, Fawkner S, Coleman S, Sanders R (2016) Automatic calculation of personal body segment parameters with a Microsoft Kinect device. In: Ae M, Enomoto Y, Fujii N, Takagi H (eds) 34 International Conference of Biomechanics in Sport 2016, pp 35–38.
  4. DIN 33402-2:2005-12 (2005) Ergonomics - Human body dimensions - Part 2: ValuesGoogle Scholar
  5. Flügel B, Greil H, Sommer K (1986) Anthropologischer Atlas. Verlag Tribüne, BerlinGoogle Scholar
  6. Hamilton MA, Quartuccio J, Mead P, Nunnally A, Lund R, Feild A (2014) Detecting key inter-joint distances and anthropometry effects for static gesture development using Microsoft Kinect. Proc Hum Factors Ergon Soc Ann Meet 58(1):2260–2264CrossRefGoogle Scholar
  7. Lun R, Zhao W (2015) A survey of applications and human recognition with Microsoft Kinect. Int J Pattern Recogn Artif Intell 29(05):1–48CrossRefGoogle Scholar
  8. Wang Q, Kurillo G, Ofli F, Bajcsy R (2015) Evaluation of pose tracking accuracy in the first and second generations of Microsoft Kinect. In: Balakrishnan P (ed) IEEE International Conference on Healthcare Informatics (ICHI). IEEE Computer Society, Dallas, pp 380–389Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Sabine Wenzel
    • 1
    Email author
  • Juliana Buchwald
    • 1
  • Hartmut Witte
    • 1
  1. 1.Biomechatronics GroupTechnische Universität IlmenauIlmenauGermany

Personalised recommendations