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.
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Bloisi, D.D., Iocchi, L. (2008). Rek-Means: A k-Means Based Clustering Algorithm. In: Gasteratos, A., Vincze, M., Tsotsos, J.K. (eds) Computer Vision Systems. ICVS 2008. Lecture Notes in Computer Science, vol 5008. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79547-6_11
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DOI: https://doi.org/10.1007/978-3-540-79547-6_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-79546-9
Online ISBN: 978-3-540-79547-6
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