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» Recognition of Parametrised Models from 3D Data
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128
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ICIP
2004
IEEE
16 years 3 months ago
Markerless motion capture with single and multiple cameras
The aim of Optical Motion Capture is to sequentially estimate the true state X of the subject (generally an articulated body) at any time instant tk from a set of data Dk, capture...
Paris Kaimakis, Joan Lasenby
CVPR
2012
IEEE
13 years 4 months ago
The use of on-line co-training to reduce the training set size in pattern recognition methods: Application to left ventricle seg
The use of statistical pattern recognition models to segment the left ventricle of the heart in ultrasound images has gained substantial attention over the last few years. The mai...
Gustavo Carneiro, Jacinto C. Nascimento
CA
2003
IEEE
15 years 6 months ago
Melting and Flowing of Viscous Volumes
We present a simple, linear 3D cellular automata approach for animating the melting process of solid volumetric models. Accurate modelling of object melting usually requires compl...
Xiaoming Wei, Wei Li, Arie E. Kaufman
133
Voted
IPSN
2010
Springer
15 years 3 months ago
Collaborative signal processing for action recognition in body sensor networks: a distributed classification algorithm using mot
Body sensor networks are emerging as a promising platform for remote human monitoring. With the aim of extracting bio-kinematic parameters from distributed body-worn sensors, thes...
Hassan Ghasemzadeh, Vitali Loseu, Roozbeh Jafari
JMLR
2006
143views more  JMLR 2006»
15 years 1 months ago
Segmental Hidden Markov Models with Random Effects for Waveform Modeling
This paper proposes a general probabilistic framework for shape-based modeling and classification of waveform data. A segmental hidden Markov model (HMM) is used to characterize w...
Seyoung Kim, Padhraic Smyth