TY - GEN
T1 - Infinite hidden Markov models and ISA features for unusual-event detection in video
AU - Pruteanu-Malinici, Iulian
AU - Carin, Lawrence
N1 - Generated from Scopus record by KAUST IRTS on 2021-02-09
PY - 2007/1/1
Y1 - 2007/1/1
N2 - We address the problem of unusual-event detection in a video sequence. Invariant subspace analysis (ISA) is used to extract features from the video, and the time-evolving properties of these features are modeled via an infinite hidden Markov model (iHMM), which is trained using "normal"/ "typical" video data. The iHMM automatically determines the proper number of HMM states, and it retains a full posterior density function, on all model parameters. Anomalies (unusual events) are detected subsequently if a low likelihood is observed when associated sequential features are submitted to the trained iHMM. A hierarchical Dirichlet process (HDP) framework is employed in the formulation of the iHMM. The evaluation of posterior distributions for the iHMM is achieved in two ways: via MCMC and using a variational Bayes (VB) formulation. ©2007 IEEE.
AB - We address the problem of unusual-event detection in a video sequence. Invariant subspace analysis (ISA) is used to extract features from the video, and the time-evolving properties of these features are modeled via an infinite hidden Markov model (iHMM), which is trained using "normal"/ "typical" video data. The iHMM automatically determines the proper number of HMM states, and it retains a full posterior density function, on all model parameters. Anomalies (unusual events) are detected subsequently if a low likelihood is observed when associated sequential features are submitted to the trained iHMM. A hierarchical Dirichlet process (HDP) framework is employed in the formulation of the iHMM. The evaluation of posterior distributions for the iHMM is achieved in two ways: via MCMC and using a variational Bayes (VB) formulation. ©2007 IEEE.
UR - http://ieeexplore.ieee.org/document/4379784/
UR - http://www.scopus.com/inward/record.url?scp=48149102321&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2007.4379784
DO - 10.1109/ICIP.2007.4379784
M3 - Conference contribution
SN - 1424414377
BT - Proceedings - International Conference on Image Processing, ICIP
PB - IEEE Computer [email protected]
ER -