Name
Abstract | ||
|---|---|---|
Driver fatigue is a major cause of traffic accidents. The fatigue detection systems based on computer vision have great potential given its property of non-invasiveness. Major challenges that arise are fast movements of eyes and mouth, changes in pose and lighting variations. In this paper an Active Shape Model is presented for facial features detection of features extracted from the parametric model Candide-3. We describe the characterization methodology from parametric model. Also quantitatively evaluated the accuracy for feature detection and estimation of the parameters associated with fatigue, analyzing its robustness to variations in pose and local variations in the regions of interest. The model used and characterization methodology showed efficient to detect fatigue in 100% of the cases. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-17277-9_18 | ISVC (3) |
Keywords | Field | DocType |
major cause,fatigue detection system,active shape model,parametric model candide-3,parametric model,driver fatigue,characterization methodology,major challenge,feature detection,facial features detection,feature extraction,computer vision,region of interest | Active shape model,Computer vision,Parametric model,Feature detection,Pattern recognition,Computer science,Robustness (computer science),Artificial intelligence,Intelligent transportation system | Conference |
Volume | ISSN | ISBN |
6455 | 0302-9743 | 3-642-17276-8 |
Citations | PageRank | References |
3 | 0.44 | 12 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hernán García | 1 | 3 | 0.77 |
| Augusto Salazar | 2 | 50 | 9.47 |
| Damián Alvarez | 3 | 3 | 0.77 |
| Álvaro Á. Orozco | 4 | 16 | 12.88 |