Name
Abstract | ||
|---|---|---|
One of the most major causes of road crashes is the fatigue. In this paper it is shown a methodology for Driver Fatigue assessment based on computer vision (CV). CV is used to characterize different visual responses of the driver while driving and suffering from fatigue. Some of the visual responses are the eyelid and lips movements. The proposed Methodology uses an active appereance model (AAM) to adjust the facial model Candide3 from images sequences where spatial measures can be computed. These measures include the eye closeness and the mouth openness. Results show that with the measures computed it's possible efficiently extract some discriminant parameters related to driver fatigue state. For example, the PERCLOS, the AECS, and the YawnFrec. Finally, an experimental framework is designed in order to compare the performance of the proposed method with psychological signal-based methods. |
Year | Venue | Keywords |
|---|---|---|
2010 | ICINCO (1) | Driver fatigue |
Field | DocType | Citations |
Data mining,Control engineering,Feature extraction,Engineering | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Damián Alvarez | 1 | 3 | 0.77 |
| Álvaro Á. Orozco | 2 | 16 | 12.88 |
| Augusto Salazar | 3 | 0 | 0.34 |