Multiple classifier combination using reject options and markov fusion networks
Michael Glodek, Martin Schels, Günther Palm, Friedhelm Schwenker · 2012
The audio/visual emotion challenge (AVEC) resembles a benchmarking data collection in order to evaluate and develop techniques for the recognition of affective states. In our work, we present a Markov fusion network (MFN) for the combination of different individual classifiers, that is derived from the well-known Markov random fields (MRF). It is capable to restore missing values from a sequence of decisions and can integrate multiple channels and weights them dynamically using confidences. The approach shows promising challenge results compared to the baseline.