A Discriminative Framework for Anomaly Detection in Large Videos

28 Sep 2016Allison Del GiornoJ. Andrew BagnellMartial Hebert

We address an anomaly detection setting in which training sequences are unavailable and anomalies are scored independently of temporal ordering. Current algorithms in anomaly detection are based on the classical density estimation approach of learning high-dimensional models and finding low-probability events... (read more)

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