http://www.cnr.it/ontology/cnr/individuo/prodotto/ID287691
A Statistical Approach to Automatically Detect How Many Persons Appear in a Video (Articolo in rivista)
- Type
- Label
- A Statistical Approach to Automatically Detect How Many Persons Appear in a Video (Articolo in rivista) (literal)
- Anno
- 2014-01-01T00:00:00+01:00 (literal)
- Alternative label
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Dario Cazzato; Marco Leo; Cosimo Distante (literal)
- Pagina inizio
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
- http://www.scipublish.com/journals/ISA/papers/249 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Rivista
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- University of Salento, Lecce, Italy;
National Research Council of Italy Institute of Optics, Arnesano, Italy (literal)
- Titolo
- A Statistical Approach to Automatically Detect How Many Persons Appear in a Video (literal)
- Abstract
- Face indexing is a very popular research topic and it has been investigated over the last 10 years. It can be used for a wide range of applications such as automatic video content analysis, data mining, video annotation and labeling, etc. In this work a statistical approach to address this challenging issue is presented: the number of persons that are present in a generic video (even having low resolution and/or taken from a mobile camera) is automatically detected and also the intervals of frames in which each person appears are extracted. The main contributions of the proposed work are that no initializations neither a priory knowledge about the scene contents are required. Moreover, this approach introduces a generalized version of the k-means method that, through different statistical indices, automatically determines the number of people in the scene. (literal)
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