Dynamic Hierarchical Dirichlet Process for Anomaly Detection in Video
This is a source code and synthetic data for dynamic hierarchical Dirichlet process for anomaly detection in video, introduced in O.Isupova, D.Kuzin, L.Mihaylova "Dynamic Hierarchical Dirichlet Process for Abnormal Behaviour Detection in Video" in Proceedings of 19th International Conference of Information Fusion, Heidelberg, Germany, July 2016.
In this approach we consider the problem of anomaly detection as extracting typical motion patterns from data by topic modeling methods and detect video clips as abnormal if they have low values of likelihood computed with respect to these extracted typical motion patterns. Learning and inference is performed in a fully unsupervised manner.
If you use this code or model please cite the above mentioned paper.