Detection of Deception in the Mafia Party Game

The problem of deception detection is very challenging. Only trained people with specialist knowledge are able to demonstrate an accuracy that is sufficiently higher than random predictions. We present a multi-stage automatic system for extracting features from facial cues and evaluate it on the Mafia game database which we have collected. It is a large database of truthful and deceptive people, recorded in conditions more variable and realistic than many other databases of similar kind. We demonstrate that using the extracted features we are able to correctly classify instances with an average AUC (area under the ROC curve) equal to 0.61, significantly better than random predictions.