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» Structure From Motion Using Sequential Monte Carlo Methods
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NIPS
2001
13 years 6 months ago
Sequential Noise Compensation by Sequential Monte Carlo Method
We present a sequential Monte Carlo method applied to additive noise compensation for robust speech recognition in time-varying noise. The method generates a set of samples accord...
K. Yao, S. Nakamura
CVPR
2005
IEEE
14 years 7 months ago
Appearance-Guided Particle Filtering for Articulated Hand Tracking
We propose a model-based tracking method, called appearance-guided particle filtering (AGPF), which integrates both sequential motion transition information and appearance informa...
Wen-Yan Chang, Chu-Song Chen, Yi-Ping Hung
SAC
2008
ACM
13 years 4 months ago
Particle methods for maximum likelihood estimation in latent variable models
Standard methods for maximum likelihood parameter estimation in latent variable models rely on the Expectation-Maximization algorithm and its Monte Carlo variants. Our approach is ...
Adam M. Johansen, Arnaud Doucet, Manuel Davy
ICPR
2004
IEEE
14 years 6 months ago
Articulate Hand Motion Capturing Based on a Monte Carlo Nelder-Mead Simplex Tracker
This paper presents an algorithm for tracking the articulate hand motion in monocular video sequences. The task is challenging due to the high degrees of freedom involved in the h...
John Lin, Thomas S. Huang, Ying Wu
ICAT
2003
IEEE
13 years 10 months ago
Head Motion Prediction in Augmented Reality Systems Using Monte Carlo Particle Filters
A basic problem with Augmented Reality systems using Head-Mounted Displays (HMDs) is the perceived latency or lag. This delay corresponds to the elapsed time between the moment wh...
Fakhreddine Ababsa, Jean-Yves Didier, Malik Mallem...