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Many clustering methods are designed for especial cluster types or have good performance dealing with particular size and shape of clusters. The main problem in this connection is how to define a similarity (or dissimilarity) criterion to make an algorithm ...
We present an algorithm for clustering sets of detected interest points into groups that correspond to visually distinct structure. Through the use of a suitable colour and texture representation, our clustering method is able to identify keypoints that be ...
Data alone are worth almost nothing. While data collection is increasing exponentially worldwide, a clear distinction between retrieving data and obtaining knowledge has to be made. Data are retrieved while measuring phenomena or gathering facts. Knowledge ...
The problem of feature selection has been thoroughly analyzed in the context of pattern classification, with the purpose of avoiding the curse of dimensionality. However, in the context of multimodal signal processing, this problem has been studied less. O ...
This paper aims at investigating the use of sequential clustering for speaker diarization. Conventional diarization systems are based on parametric models and agglomerative clustering. In our previous work we proposed a non-parametric method based on the a ...
One of the shortcomings of the existing clustering methods is their problems dealing with different shape and size clusters. On the other hand, most of these methods are designed for especial cluster types or have good performance dealing with particular s ...
This paper aims at investigating the use of sequential clustering for speaker diarization. Conventional diarization systems are based on parametric models and agglomerative clustering. In our previous work we proposed a non-parametric method based on the a ...
The extension of the likelihood method of Süveges (Extremes, 2007) is presented. The extension allows for finding independent clusters of extreme events and determining the range of dependence on extremal levels, and estimate clustering characteristic of t ...
In this paper we propose to use clustering methods for automatic counting of pedestrians in video sequences. As input, we consider the output of those detection/ tracking systems that overestimate the number of targets. Clustering techniques are applied to ...
We address the issue of how statistical and information-theoric measures can be employed to quantify the categorization process of a simulated robotic agent interacting with its local environment. We show how correlation, entropy, and mutual information ca ...