Mapping dynamic Bayesian networks to α-shapes: application to human faces identification across ages.

We propose a new method to improve dynamic Bayesian networks (DBNs) classification power by mapping them to geometric α-shapes. This approach enhances facial identification accuracy by revealing topological signatures and outperforming existing models.