Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloA visual approach for driver inattention detection
Anno di pubblicazione2007
Formato-
Autore/iTiziana D'Orazio; Marco Leo; Cataldo Guaragnella; Arcangelo Distante
Affiliazioni autoriISSIA-CNR, DEE-Politecnico di Bari
Autori CNR e affiliazioni
  • ARCANGELO DISTANTE
  • TIZIANA RITA D'ORAZIO
  • MARCO LEO
Lingua/e-
AbstractMonitoring driver fatigue, inattention, and lack of sleep is very important in preventing motor vehicles accidents. A visual system for automatic driver vigilance has to address two fundamental problems. First of all it has to analyze the sequence of images and detect if the driver has his eyes open or closed, and then it has to evaluate the temporal occurrence of eyes open to estimate the driver's visual attention level. In this paper we propose a visual approach that solves both problems. A neural classifier is applied to recognize the eyes in the image, selecting two candidate regions that might contain the eyes by using iris geometrical information and symmetry. The novelty of this work is that the algorithm works on complex images without constraints on the background, skin color segmentation and so on. Several experiments were carried out on images of subjects with different eye colors, some of them wearing glasses, in different light conditions. Tests show robustness with respect to situations such as eyes partially occluded, head rotation and so on. In particular, when applied to images where people have eyes closed the proposed algorithm correctly reveals the absence of eyes. Next, the analysis of the eye occurrence in image sequences is carried out with a probabilistic model to recognize anomalous behaviors such as driver inattention or sleepiness. Image sequences acquired in the laboratory and while people were driving a car were used to test the driver behavior analysis and demonstrate the effectiveness of the whole approach.
Lingua abstract-
Altro abstract-
Lingua altro abstract-
Pagine da2341
Pagine a2355
Pagine totali-
RivistaPattern recognition
Attiva dal 1968
Editore: Pergamon Press. - New York
Paese di pubblicazione: Regno Unito
Lingua: inglese
ISSN: 0031-3203
Titolo chiave: Pattern recognition
Titolo proprio: Pattern recognition.
Titolo abbreviato: Pattern recogn.
Numero volume della rivista40
Fascicolo della rivista-
DOI-
Verificato da referee-
Stato della pubblicazione-
Indicizzazione (in banche dati controllate)
  • ISI Web of Science (WOS) (Codice:000246534800019)
  • Scopus (Codice:2-s2.0-34147139802)
Parole chiaveiris detection, behavior analysis, neural network, mixture Gaussian model
Link (URL, URI)-
Titolo parallelo-
Licenza-
Scadenza embargo-
Data di accettazione-
Note/Altre informazioni-
Strutture CNR
  • ISSIA — Istituto di studi sui sistemi intelligenti per l'automazione
Moduli/Attività/Sottoprogetti CNR
  • SP.P06.004.001 : Sistemi Intelligenti per la sicurezza
Progetti Europei-
Allegati
Articolo pubblicato (documento privato )
Tipo documento: application/pdf

Dati storici
I dati storici non sono modificabili, sono stati ereditati da altri sistemi (es. Gestione Istituti, PUMA, ...) e hanno solo valore storico.
Area disciplinareComputer Science & Engineering
Area valutazione CIVRIngegneria industriale e informatica
Rivista ISIPATTERN RECOGNITION [74558J0]