An adaptive parallel background model for high-throughput video applications and smart cameras embedding (Contributo in atti di convegno)

Type

• Contributo in atti di convegno (Classe)
• Prodotto della ricerca (Classe)

Label

• An adaptive parallel background model for high-throughput video applications and smart cameras embedding (Contributo in atti di convegno) (literal)

Anno

• 2014-01-01T00:00:00+01:00 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi

• 10.1145/2659021.2659059 (literal)

Alternative label

• Renò, Vito; Marani, Roberto; D'Orzazio, T.; Stella, Ettore; Nitti, Massimiliano (2014)
  An adaptive parallel background model for high-throughput video applications and smart cameras embedding
  in ICDSC 2014
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• Renò, Vito; Marani, Roberto; D'Orzazio, T.; Stella, Ettore; Nitti, Massimiliano (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url

• http://www.scopus.com/record/display.url?eid=2-s2.0-84913573386&origin=inward (literal)

Note

• Scopu (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• Istituto Di Studi Sui Sistemi Intelligenti Per L'automazione, Bari (literal)

Titolo

• An adaptive parallel background model for high-throughput video applications and smart cameras embedding (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn

• 9781450329255 (literal)

Abstract

• Background (BG) modelling is a key task in every computer vision system (CVS) independently of the final purpose for which it is designed. Even if many BG approaches exist (for example Mixture of Gaussians or Eigenbackground), they can not efficiently process real time videos due to the model complexity and to the high throughput of the video flux. One of the most challenging real time applications is the athletic scene processing, because, in this context, there are many critical aspects for defining a BG model: no a-priori knowledge of the static scene, sudden illumination changes and many moving objects that slow down the upgrade phase. The aim of this work is to provide an adaptive BG model able to deal with high frame rate videos (>= 100 fps) in real time processing, and suitable for smart cameras embedding, finding a good compromise between the model complexity and its responsiveness. Real experiments demonstrate that this BG model approach shows great performances and robustness during the real time processing of athletic video frames, up to 100 fps. Copyright 2014 ACM. (literal)

Prodotto di

• Sistemi Sensoriali per il Controllo di Qualità e Diagnostica (SP.P03.002.001) (Modulo)
• Institute of intelligent systems for automation (ISSIA) (Istituto)

Autore CNR

• ETTORE STELLA (Unità di personale interno)
• TIZIANA RITA D'ORAZIO (Persona)
• ROBERTO MARANI (Persona)
• MASSIMILIANO NITTI (Unità di personale interno)

Insieme di parole chiave

• Keywords of "An adaptive parallel background model for high-throughput video applications and smart cameras embedding" (Insieme di parole chiave)

Incoming links:

Prodotto

• Institute of intelligent systems for automation (ISSIA) (Istituto)
• Sistemi Sensoriali per il Controllo di Qualità e Diagnostica (SP.P03.002.001) (Modulo)

Autore CNR di

• TIZIANA RITA D'ORAZIO (Persona)
• ETTORE STELLA (Unità di personale interno)
• MASSIMILIANO NITTI (Unità di personale interno)
• http://www.cnr.it/ontology/cnr/individuo/unitaDiPersonaleEsterno/ID23466
• ROBERTO MARANI (Persona)

Insieme di parole chiave di

• Keywords of "An adaptive parallel background model for high-throughput video applications and smart cameras embedding" (Insieme di parole chiave)