Semi-supervised adapted HMMs for unusual event detection

• Published in: 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) Vol. 1; pp. 611 - 618 vol. 1
• Main Authors: Dong Zhang, Gatica-Perez, D., Bengio, S., McCowan, I.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 2005
• Subjects: Ambient intelligence; Bayesian methods; Computer vision; Data mining; Event detection; Hidden Markov models; Information management; Streaming media; Surveillance; Training data

We address the problem of temporal unusual event detection. Unusual events are characterized by a number of features (rarity, unexpectedness, and relevance) that limit the application of traditional supervised model-based approaches. We propose a semi-supervised adapted hidden Markov model (HMM) fra...