In this paper we present a new clustering method based on k-means that has been implemented on a video surveillance system. Rek-means does not require to specify in advance the number of clusters to search for and is more precise than k-means in clustering data coming from multiple Gaussian distributions with different co-variances, while maintaining real-time performance. Experiments on real and synthetic datasets are presented to measure the effectiveness and the performance of the proposed method. © 2008 Springer-Verlag Berlin Heidelberg.
Rek-Means: A k-Means Based Clustering Algorithm / Bloisi, Domenico Daniele; Iocchi, Luca. - 5008:(2008), pp. 109-118. (Intervento presentato al convegno 6th Int. Conf. on Computer Vision Systems (ICVS tenutosi a Santorini; Greece nel maggio 2008) [10.1007/978-3-540-79547-6_11].
Rek-Means: A k-Means Based Clustering Algorithm
BLOISI, Domenico Daniele;IOCCHI, Luca
2008
Abstract
In this paper we present a new clustering method based on k-means that has been implemented on a video surveillance system. Rek-means does not require to specify in advance the number of clusters to search for and is more precise than k-means in clustering data coming from multiple Gaussian distributions with different co-variances, while maintaining real-time performance. Experiments on real and synthetic datasets are presented to measure the effectiveness and the performance of the proposed method. © 2008 Springer-Verlag Berlin Heidelberg.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
