Subspace eyetracking for driver warning

Fernando De la Torre; Carlos Javier Garcia Rubio; Elisa Martínez

doi:10.1109/ICIP.2003.1247248

Subspace eyetracking for driver warning

Fernando De la Torre
, Carlos Javier Garcia Rubio
, Elisa Martínez

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

7 Citations (Scopus)

91 Downloads (Pure)

Abstract

Driver's fatigue/distraction is one of the most common causes of traffic accidents. The aim of this paper is to develop a real time system to detect anomalous situations while driving. In a learning stage, the user will sit in front of the camera and the system will learn a person-specific facial appearance model (PSFAM) in an automatic manner. The PSFAM will be used to perform gaze detection and eye-activity recognition in a real time based on subspace constraints. Preliminary experiments measuring the PERCLOS index (average time that the eyes are closed) under a variety of conditions are reported.

Original language	English
Title of host publication	IEEE International Conference on Image Processing
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	329-332
Number of pages	4
Volume	3
ISBN (Print)	9780780377508
DOIs	https://doi.org/10.1109/ICIP.2003.1247248
Publication status	Published - 14 Sept 2003
Externally published	Yes
Event	Proceedings: 2003 International Conference on Image Processing, ICIP-2003 - Barcelona, Spain Duration: 14 Sept 2003 → 17 Sept 2003

Conference

Conference	Proceedings: 2003 International Conference on Image Processing, ICIP-2003
Country/Territory	Spain
City	Barcelona
Period	14/09/03 → 17/09/03

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

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10.1109/ICIP.2003.1247248

Conference ContributionFinal published version, 327 KB

Cite this

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title = "Subspace eyetracking for driver warning",

abstract = "Driver's fatigue/distraction is one of the most common causes of traffic accidents. The aim of this paper is to develop a real time system to detect anomalous situations while driving. In a learning stage, the user will sit in front of the camera and the system will learn a person-specific facial appearance model (PSFAM) in an automatic manner. The PSFAM will be used to perform gaze detection and eye-activity recognition in a real time based on subspace constraints. Preliminary experiments measuring the PERCLOS index (average time that the eyes are closed) under a variety of conditions are reported.",

keywords = "Eye movements, Highway accidents, Human computer interaction, Learning systems, Optical flows, Principal component analysis, Real time systems",

author = "\{De la Torre\}, Fernando and Rubio, \{Carlos Javier Garcia\} and Elisa Mart{\'i}nez",

year = "2003",

month = sep,

day = "14",

doi = "10.1109/ICIP.2003.1247248",

language = "English",

isbn = "9780780377508",

volume = "3",

pages = "329--332",

booktitle = "IEEE International Conference on Image Processing",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States",

note = "Proceedings: 2003 International Conference on Image Processing, ICIP-2003 ; Conference date: 14-09-2003 Through 17-09-2003",

}

TY - GEN

T1 - Subspace eyetracking for driver warning

AU - De la Torre, Fernando

AU - Rubio, Carlos Javier Garcia

AU - Martínez, Elisa

PY - 2003/9/14

Y1 - 2003/9/14

N2 - Driver's fatigue/distraction is one of the most common causes of traffic accidents. The aim of this paper is to develop a real time system to detect anomalous situations while driving. In a learning stage, the user will sit in front of the camera and the system will learn a person-specific facial appearance model (PSFAM) in an automatic manner. The PSFAM will be used to perform gaze detection and eye-activity recognition in a real time based on subspace constraints. Preliminary experiments measuring the PERCLOS index (average time that the eyes are closed) under a variety of conditions are reported.

AB - Driver's fatigue/distraction is one of the most common causes of traffic accidents. The aim of this paper is to develop a real time system to detect anomalous situations while driving. In a learning stage, the user will sit in front of the camera and the system will learn a person-specific facial appearance model (PSFAM) in an automatic manner. The PSFAM will be used to perform gaze detection and eye-activity recognition in a real time based on subspace constraints. Preliminary experiments measuring the PERCLOS index (average time that the eyes are closed) under a variety of conditions are reported.

KW - Eye movements

KW - Highway accidents

KW - Human computer interaction

KW - Learning systems

KW - Optical flows

KW - Principal component analysis

KW - Real time systems

UR - https://www.scopus.com/pages/publications/0344703608

U2 - 10.1109/ICIP.2003.1247248

DO - 10.1109/ICIP.2003.1247248

M3 - Conference contribution

AN - SCOPUS:0344703608

SN - 9780780377508

VL - 3

SP - 329

EP - 332

BT - IEEE International Conference on Image Processing

PB - IEEE, Institute of Electrical and Electronics Engineers

T2 - Proceedings: 2003 International Conference on Image Processing, ICIP-2003

Y2 - 14 September 2003 through 17 September 2003

ER -

Subspace eyetracking for driver warning

Abstract

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UN SDGs

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