- Tytuł:
- A quaternion clustering framework
- Autorzy:
-
Piórek, Michał
Jabłoński, Bartosz - Powiązania:
- https://bibliotekanauki.pl/articles/330038.pdf
- Data publikacji:
- 2020
- Wydawca:
- Uniwersytet Zielonogórski. Oficyna Wydawnicza
- Tematy:
-
data clustering
quaternions data processing
human gait
data processing
grupowanie danych
chód człowieka
przetwarzanie danych - Opis:
- 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.
- Źródło:
-
International Journal of Applied Mathematics and Computer Science; 2020, 30, 1; 133-147
1641-876X
2083-8492 - Pojawia się w:
- International Journal of Applied Mathematics and Computer Science
- Dostawca treści:
- Biblioteka Nauki
Artykuł