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» Melody Spotting Using Hidden Markov Models
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ICIP
2004
IEEE
16 years 6 months ago
Action modeling with volumetric data
In this paper we propose and test an action recognition algorithm in which the images of the scene captured by a significant number of cameras are first used to generate a volumet...
Fabio Cuzzolin, Augusto Sarti, Stefano Tubaro
INTERSPEECH
2010
14 years 11 months ago
Deep-structured hidden conditional random fields for phonetic recognition
We extend our earlier work on deep-structured conditional random field (DCRF) and develop deep-structured hidden conditional random field (DHCRF). We investigate the use of this n...
Dong Yu, Li Deng
151
Voted
ATAL
2006
Springer
15 years 8 months ago
Learning executable agent behaviors from observation
We present a method for learning a human understandable, executable model of an agent's behavior using observations of its interaction with the environment. By executable we ...
Andrew Guillory, Hai Nguyen, Tucker R. Balch, Char...
ICCV
2009
IEEE
15 years 2 months ago
Segmentation, ordering and multi-object tracking using graphical models
In this paper, we propose a unified graphical-model framework to interpret a scene composed of multiple objects in monocular video sequences. Using a single pairwise Markov random...
Chaohui Wang, Martin de La Gorce, Nikos Paragios
CVPR
2007
IEEE
16 years 6 months ago
Discriminative Learning of Dynamical Systems for Motion Tracking
We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
Minyoung Kim, Vladimir Pavlovic