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CVPR
2004
IEEE
14 years 26 days ago
Modeling Complex Motion by Tracking and Editing Hidden Markov Graphs
In this paper, we propose a generative model for representing complex motion, such as wavy river, dancing fire and dangling cloth. Our generative method consists of four component...
Yizhou Wang, Song Chun Zhu
CVPR
2009
IEEE
15 years 4 months ago
Learning to Track with Multiple Observers
We propose a novel approach to designing algorithms for object tracking based on fusing multiple observation models. As the space of possible observation models is too large for...
Björn Stenger, Roberto Cipolla, Thomas Woodle...
STAIRS
2008
175views Education» more  STAIRS 2008»
13 years 10 months ago
Learning Process Behavior with EDY: an Experimental Analysis
This paper presents an extensive evaluation, on artificial datasets, of EDY, an unsupervised algorithm for automatically synthesizing a Structured Hidden Markov Model (S-HMM) from ...
Ugo Galassi
BMCBI
2010
145views more  BMCBI 2010»
13 years 9 months ago
Clustering metagenomic sequences with interpolated Markov models
Background: Sequencing of environmental DNA (often called metagenomics) has shown tremendous potential to uncover the vast number of unknown microbes that cannot be cultured and s...
David R. Kelley, Steven L. Salzberg
CLEF
2009
Springer
13 years 10 months ago
Morphological Analysis by Multiple Sequence Alignment
In biological sequence processing, Multiple Sequence Alignment (MSA) techniques capture information about long-distance dependencies and the three-dimensional structure of protein ...
Tzvetan Tchoukalov, Christian Monson, Brian Roark