TY - GEN
T1 - Hypovigilance detection by calculating and analyzing a spatio-temporal features of the face components based on 3D head orientation
AU - Akrout, Belhassen
AU - Mahdi, Walid
PY - 2014
Y1 - 2014
N2 - The Drowsiness is the risk to fall asleep for one moment with the closed eyes, it is an intermediate state between the awake and the sleep. This state is involuntary and it is accompanied by a fall of vigilance. Consequently, the development of a system for the automatic control of driver tiredness, to prevent the driver in advance of the accidents, received an interest growing of research mediums. In this work, we propose an approache of drowsiness detection which makes it possible to determine the 3D head orientation to capture the lack of concentration states. This approach is based on the estimate of the head rotation angles in the three directions Y aw, Pitch and Roll by exploiting only three interest points of the face. The approache suggested are evaluated by the MiraclHB database. The evaluation show many promising results and show the effectiveness of the approache suggested.
AB - The Drowsiness is the risk to fall asleep for one moment with the closed eyes, it is an intermediate state between the awake and the sleep. This state is involuntary and it is accompanied by a fall of vigilance. Consequently, the development of a system for the automatic control of driver tiredness, to prevent the driver in advance of the accidents, received an interest growing of research mediums. In this work, we propose an approache of drowsiness detection which makes it possible to determine the 3D head orientation to capture the lack of concentration states. This approach is based on the estimate of the head rotation angles in the three directions Y aw, Pitch and Roll by exploiting only three interest points of the face. The approache suggested are evaluated by the MiraclHB database. The evaluation show many promising results and show the effectiveness of the approache suggested.
KW - 3D Head pose estimation
KW - Drowsiness detection
KW - Human safety
KW - Intelligent vehicle
UR - https://www.scopus.com/pages/publications/84903756878
U2 - 10.1109/ATSIP.2014.6834593
DO - 10.1109/ATSIP.2014.6834593
M3 - Conference contribution
AN - SCOPUS:84903756878
SN - 9781479948888
T3 - 2014 1st International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2014
SP - 137
EP - 142
BT - 2014 1st International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2014
PB - IEEE Computer Society
T2 - 1st International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2014
Y2 - 17 March 2014 through 19 March 2014
ER -
