Subspace eyetracking for driver warning

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 eyeactivity 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.

• Type: Conference
• Year: 2003
• Where: ICIP
• Authors: Fernando De la Torre, Carlos Javier Garcia Rubio, Elisa Martínez
• Keywords: Anomalous Situations, ICIP 2003, Image Processing, Person-specific Facial Appearance, Real Time