@inproceedings{f66cf30bf0f54909aa841188e20cfde1,
title = "Wavelet features in motion data classification",
abstract = "The paper deals with the problem of motion data classification based on result of multiresolution analysis implemented in form of quaternion lifting scheme. Scheme processes directly on time series of rotations coded in form of unit quaternion signal. In the work new features derived from wavelet energy and entropy are proposed. To validate the approach gait database containing data of 30 different humans is used. The obtained results are satisfactory. The classification has over than 91\% accuracy.",
keywords = "feature extraction, gait identification, lifting scheme, motion capture, motion data classification, multiresolution analysis, wavelet energy, wavelet entropy",
author = "Agnieszka Szczȩsna and Adam {\'S}wito{\'n}ski and Janusz S{\l}upik and Henryk Josi{\'n}ski and Konrad Wojciechowski",
note = "Publisher Copyright: {\textcopyright} 2016 Author(s).; International Conference of Numerical Analysis and Applied Mathematics 2015, ICNAAM 2015 ; Conference date: 23-09-2015 Through 29-09-2015",
year = "2016",
month = jun,
day = "8",
doi = "10.1063/1.4951957",
language = "English",
series = "AIP Conference Proceedings",
publisher = "American Institute of Physics Inc.",
editor = "Simos, \{Theodore E.\} and Simos, \{Theodore E.\} and Charalambos Tsitouras and Simos, \{Theodore E.\}",
booktitle = "International Conference of Numerical Analysis and Applied Mathematics 2015, ICNAAM 2015",
address = "United States",
}