Abstract
We propose a method for clustering and key points selection. We have shown that the proposed clustering based on the voting maximization scheme has advantages concerning the cluster’s compactness, working well for clusters of different densities and/or sizes. Experimental results demonstrate the high performance of the proposed scheme and its application to video summarization problem.
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Panagiotakis, C., Fragopoulou, P. (2013). Voting Clustering and Key Points Selection. In: Wilson, R., Hancock, E., Bors, A., Smith, W. (eds) Computer Analysis of Images and Patterns. CAIP 2013. Lecture Notes in Computer Science, vol 8047. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40261-6_53
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DOI: https://doi.org/10.1007/978-3-642-40261-6_53
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40260-9
Online ISBN: 978-3-642-40261-6
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