Likelihood Ratio-Based Detection of Facial Features

One of the first steps in face recognition, after image acquisition, is registration. A simple but effective technique of registration is to align facial features, such as eyes, nose and mouth, as well as possible to a standard face. This requires an accurate automatic estimate of the locations of those features. This contribution proposes a method for estimating the locations of facial features based on likelihood ratio-based detection. A post-processing step that evaluates the topology of the facial features is added to reduce the number of false detections. Although the individual detectors only have a reasonable performance (equal error rates range from 3.3% for the eyes to 1.0% for the nose), the positions of the facial features are estimated correctly in 95% of the face images

De cardiologische patiëntenstroom : een simulatiemodel

Een beperkte capaciteit en een grote wisselende stroom van patiënten kan leiden tot organisatorische problemen. Het ziekenhuis Rivierenland Tiel gebruikte een simulatiemodel om de knelpunten in kaart te brengen