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» Mining Trajectory Patterns Using Hidden Markov Models
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ICDCS
2012
IEEE
13 years 8 days ago
FindingHuMo: Real-Time Tracking of Motion Trajectories from Anonymous Binary Sensing in Smart Environments
Abstract—In this paper we have proposed and designed FindingHuMo (Finding Human Motion), a real-time user tracking system for Smart Environments. FindingHuMo can perform device-f...
Debraj De, Wen-Zhan Song, Mingsen Xu, Cheng-Liang ...
IDEAL
2004
Springer
15 years 3 months ago
Stock Trading by Modelling Price Trend with Dynamic Bayesian Networks
We study a stock trading method based on dynamic bayesian networks to model the dynamics of the trend of stock prices. We design a three level hierarchical hidden Markov model (HHM...
Jangmin O, Jae Won Lee, Sung-Bae Park, Byoung-Tak ...
ICASSP
2008
IEEE
15 years 4 months ago
Gradient steepness metrics using extended Baum-Welch transformations for universal pattern recognition tasks
In many pattern recognition tasks, given some input data and a family of models, the “best” model is defined as the one which maximizes the likelihood of the data given the m...
Tara N. Sainath, Dimitri Kanevsky, Bhuvana Ramabha...
MVA
2007
179views Computer Vision» more  MVA 2007»
14 years 9 months ago
Multi-object trajectory tracking
The majority of existing tracking algorithms are based on the maximum a posteriori (MAP) solution of a probabilistic framework using a Hidden Markov Model, where the distribution ...
Mei Han, Wei Xu, Hai Tao, Yihong Gong
VLSISP
2010
191views more  VLSISP 2010»
14 years 4 months ago
Sign Language Phoneme Transcription with Rule-based Hand Trajectory Segmentation
A common approach to extract phonemes of sign language is to use an unsupervised clustering algorithm to group the sign segments. However, simple clustering algorithms based on dis...
W. W. Kong, Surendra Ranganath