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124
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JMLR
2010
129views more  JMLR 2010»
14 years 10 months ago
Approximation of hidden Markov models by mixtures of experts with application to particle filtering
Selecting conveniently the proposal kernel and the adjustment multiplier weights of the auxiliary particle filter may increase significantly the accuracy and computational efficie...
Jimmy Olsson, Jonas Ströjby
135
Voted
PSIVT
2007
Springer
118views Multimedia» more  PSIVT 2007»
15 years 9 months ago
Vision-Based Guitarist Fingering Tracking Using a Bayesian Classifier and Particle Filters
This paper presents a vision-based method for tracking guitar fingerings played by guitar players from stereo cameras. We propose a novel framework for colored finger markers track...
Chutisant Kerdvibulvech, Hideo Saito
138
Voted
CDC
2008
IEEE
157views Control Systems» more  CDC 2008»
15 years 3 months ago
A hidden Markov filtering approach to multiple change-point models
We describe a hidden Markov modeling approach to multiple change-points that has attractive computational and statistical properties. This approach yields explicit recursive filter...
Tze Leung Lai, Haipeng Xing
ICIP
2004
IEEE
16 years 5 months ago
Scalable video coding based on motion-compensated temporal filtering: complexity and functionality analysis
Video coding techniques yielding state-of-the-art compression performance require large amount of computational resources, hence practical implementations, which target a broad ma...
Fabio Verdicchio, Yiannis Andreopoulos, Tom Clerck...
IJCNN
2006
IEEE
15 years 9 months ago
A Monte Carlo Sequential Estimation for Point Process Optimum Filtering
— Adaptive filtering is normally utilized to estimate system states or outputs from continuous valued observations, and it is of limited use when the observations are discrete e...
Yiwen Wang 0002, António R. C. Paiva, Jose ...