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In video surveillance, classification of visual data can be very hard, due to the scarce resolution and the noise characterizing the sen-sors' data. In this paper, we propose a novel feature, the ARray of CO-variances (ARCO), and a multi-class classification framework operating on Riemannian manifolds. ARCO is composed by a structure of covari-ance matrices(More)
In surveillance applications, head and body orientation of people is of primary importance for assessing many behavioral traits. Unfortunately, in this context people are often encoded by a few, noisy pixels so that their characterization is difficult. We face this issue, proposing a computational framework which is based on an expressive descriptor, the(More)
A reformulation of Rawnsley's Kählerian coherent states (in the framework of geometric quantization) is used in order to investigate the interplay between their local and global properties (projective embeddings) and the relationship with Klauder quantization (via path integrals and the introduction of a metric on the classical phase space). A Klauder type(More)
  • Gerald A Goldin, Metin Gurses, Boris Konopeltchenko, Manuel De Leon, Charles-Michel Marle, Gregory L Naber +14 others
  • 2005
Geometry and Symmetry in Physics is a fully-refereed, independent international journal. It aims to facilitate the rapid dissemination, at low cost, of original research articles reporting interesting and potentially important ideas, and invited review articles providing background, perspectives, and useful sources of reference material. In addition to(More)
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