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» Learning Dynamic Event Descriptions in Image Sequences
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IICAI
2007
13 years 9 months ago
Modeling Temporal Behavior via Structured Hidden Markov Models: an Application to Keystroking Dynamics
Structured Hidden Markov Models (S-HMM) are a variant of Hierarchical Hidden Markov Models; it provides an abstraction mechanism allowing a high level symbolic description of the k...
Ugo Galassi, Attilio Giordana, Charbel Julien, Lor...
CVPR
2012
IEEE
11 years 10 months ago
Learning latent temporal structure for complex event detection
In this paper, we tackle the problem of understanding the temporal structure of complex events in highly varying videos obtained from the Internet. Towards this goal, we utilize a...
Kevin Tang, Fei-Fei Li, Daphne Koller
IJON
2006
99views more  IJON 2006»
13 years 7 months ago
Learning vector quantization: The dynamics of winner-takes-all algorithms
Winner-Takes-All (WTA) prescriptions for Learning Vector Quantization (LVQ) are studied in the framework of a model situation: Two competing prototype vectors are updated accordin...
Michael Biehl, Anarta Ghosh, Barbara Hammer
CVPR
2011
IEEE
13 years 2 months ago
Online Detection of Unusual Events in Videos via Dynamic Sparse Coding
Real-time unusual event detection in video stream has been a difficult challenge due to the lack of sufficient training information, volatility of the definitions for both norm...
Bin Zhao, Li Fei-Fei, Eric Xing
ECCV
2004
Springer
14 years 9 months ago
Spatially Homogeneous Dynamic Textures
Abstract. We address the problem of modeling the spatial and temporal second-order statistics of video sequences that exhibit both spatial and temporal regularity, intended in a st...
Gianfranco Doretto, Eagle Jones, Stefano Soatto