(untitled) (Revista de Investigaciones Universidad del Quindío, 2012)
Driving Fatigue is one of the main causes of traffic accidents. The fatigue detection systems based on com-puter vision have great potential given by the 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 Candi-de3. 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. Results show that the proposed model can effectively detect eye-blinks and yawnings. The model used and characterization methodology showed efficient to detect fatigue in 100% of the cases.