Models and methods for biometric motion identification Bartosz

Bartosz Jabłoński, Ryszard Klempous, Damian Majchrzak


Human motion is a complex signal with many different properties depending on various factors: age, gender, physical condition, emotions etc. Nevertheless there is a hypothesis which claims that human motion can be a source for biometric analysis and person identification. In the paper some methods to analyze and compare different motions are presented. Methods are examined for usefulness in motion identification. We distinguish time-series and frequency analysis for rotational signals describing mainly the motion of legs. The results of experiments are presented taking into consideration different motion representations.

Full Text:


Data publikacji: 2006-01-01 00:00:00
Data złożenia artykułu: 2016-04-27 10:15:06


Total abstract view - 276
Downloads (from 2020-06-17) - PDF - 0



  • There are currently no refbacks.

Copyright (c) 2015 Annales UMCS Sectio AI Informatica

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