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PERCOM
2003
ACM
14 years 29 days ago
Recognition of Human Activity through Hierarchical Stochastic Learning
Seeking to extend the functional capability of the elderly, we explore the use of probabilistic methods to learn and recognise human activity in order to provide monitoring suppor...
Sebastian Lühr, Hung Hai Bui, Svetha Venkates...
WSDM
2010
ACM
322views Data Mining» more  WSDM 2010»
14 years 5 months ago
Inferring Search Behaviors Using Partially Observable Markov (POM) Model
This article describes an application of the partially observable Markov (POM) model to the analysis of a large scale commercial web search log. Mathematically, POM is a variant o...
Kuansan Wang, Nikolas Gloy, Xiaolong Li
ICPR
2002
IEEE
14 years 8 months ago
Hierarchical Recognition of Intentional Human Gestures for Sports Video Annotation
We present a novel technique for the recognition of complex human gestures for video annotation using accelerometers and the hidden Markov model. Our extension to the standard hid...
Graeme S. Chambers, Svetha Venkatesh, Geoff A. W. ...
ICML
2000
IEEE
14 years 8 months ago
Maximum Entropy Markov Models for Information Extraction and Segmentation
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...
ICASSP
2010
IEEE
13 years 6 months ago
Multiple sequence alignment based bootstrapping for improved incremental word learning
We investigate incremental word learning with few training examples in a Hidden Markov Model (HMM) framework suitable for an interactive learning scenario with little prior knowle...
Irene Ayllól Clemente, Martin Heckmann, Ger...