<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Data clustering is one of the most popular methods of data mining and cluster analysis. The goal of clustering algorithms is to partition a data set into a specific number of clusters for compressing or summarizing original values. There are a variety of clustering algorithms available in the related literature. However, the research on the clustering of data parametrized by unit quaternions, which are commonly used to represent 3D rotations, is limited. In this paper we present a quaternion clustering methodology including an algorithm proposal for quaternion based k-means along with quaternion clustering quality measures provided by an enhancement of known indices and an automated procedure of optimal cluster number selection. The validity of the proposed framework has been tested in experiments performed on generated and real data, including human gait sequences recorded using a motion capture technique.</p></abstract>

Data clustering is one of the most popular methods of data mining and cluster analysis. The goal of clustering algorithms is to partition a data set into a specific number of clusters for compressing or summarizing original values. There are a variety of clustering algorithms available in the related literature. However, the research on the clustering of data parametrized by unit quaternions, which are commonly used to represent 3D rotations, is limited. In this paper we present a quaternion clustering methodology including an algorithm proposal for quaternion based k-means along with quaternion clustering quality measures provided by an enhancement of known indices and an automated procedure of optimal cluster number selection. The validity of the proposed framework has been tested in experiments performed on generated and real data, including human gait sequences recorded using a motion capture technique.

A Quaternion Clustering Framework

Wrocław University of Science and Technology

Department of Control Systems and Mechatronics

International Journal of Applied Mathematics and Computer Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"A Quaternion Clustering Framework"}

Data clustering is one of the most popular methods of data mining and cluster analysis. The goal of clustering algorithms is to partition a data set into a...

A Quaternion Clustering Framework

Data publikacji: 03 kwi 2020

Zakres stron: 133 - 147

Otrzymano: 04 sie 2018

Przyjęty: 29 lip 2019

DOI: https://doi.org/10.34768/amcs-2020-0011

Słowa kluczowe
data clustering, quaternions data processing, human gait data processing

© 2020 Michał Piórek et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

A Quaternion Clustering Framework

Data publikacji: 03 kwi 2020

Zakres stron: 133 - 147

Otrzymano: 04 sie 2018

Przyjęty: 29 lip 2019

DOI: https://doi.org/10.34768/amcs-2020-0011

Słowa kluczowedata clustering, quaternions data processing, human gait data processing

© 2020 Michał Piórek et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Słowa kluczowe
data clustering, quaternions data processing, human gait data processing