Dynamic Bayesian Network

A probabilistic graphical model that represents sequences of variables over time, extending standard Bayesian networks to handle temporal relationships. In accessibility and affective computing contexts, Dynamic Bayesian Networks are used to model how facial expressions, head movements, and other behavioral signals evolve over time, allowing systems to infer underlying mental or emotional states from observed sequences of physical cues. DBNs are particularly valuable for emotion recognition because they can handle uncertainty and combine multiple streams of evidence — such as simultaneous facial muscle movements and head gestures — to produce probabilistic estimates of a person's affective state.