This paper proposes a new clustering algorithm in the fuzzy-c-means family, which is designed to cluster time series and is particularly suited for short time series and those wit...
This paper proposes a novel method that preserves the geometrical structure created by variation of multiple factors in analysis of multiple factor models, i.e., multifactor analy...
This paper presents two novel features of an emergent data visualization method coined "cellular ants": unsupervised data class labeling and shape negotiation. This metho...
Andrew Vande Moere, Justin James Clayden, Andy Don...
In this paper, an analysis of locally linear embedding (LLE) in the context of clustering is developed. As LLE conserves the local affine coordinates of points, shape protrusions ...
Fabio Cuzzolin, Diana Mateus, David Knossow, Edmon...
Abstract. In this paper we present a novel tool for body-part segmentation and tracking in the context of multiple camera systems. Our goal is to produce robust motion cues over ti...
Fabio Cuzzolin, Diana Mateus, Edmond Boyer, Radu H...