Facial Action Unit Detection Using Deep Neural Networks in Videos

The detection of facial action unit is one of the most important sources for describing facial expressions. Some reasons such as facial expressions in the video, changes in the environment, different posed face images make it more difficult to detect facial action unit. In this work, a new approach, which is based on deep neural network, is recommended for facial action unit detection. The recommended approach uses three different types of classifier which are frame based, segment based and transition based while detecting the facial action unit. In classification stage, Motion History Images are given as input to the deep network in addition to the pixel values of images. Finally, results of three different classifiers for each frame is combined by using the Support Vector Machine. In the experiments which are done by using CK+ database, it is observed that the recommended approach gives us more successful results of detection than the recent studies in the literature.