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» Spike Train Driven Dynamical Models for Human Actions
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NECO
2007
108views more  NECO 2007»
13 years 4 months ago
Spike-Frequency Adapting Neural Ensembles: Beyond Mean Adaptation and Renewal Theories
We propose a Markov process model for spike-frequency adapting neural ensembles which synthesizes existing mean-adaptation approaches, population density methods, and inhomogeneou...
Eilif Mueller, Lars Buesing, Johannes Schemmel, Ka...
NN
2002
Springer
208views Neural Networks» more  NN 2002»
13 years 5 months ago
A spiking neuron model: applications and learning
This paper presents a biologically-inspired, hardware-realisable spiking neuron model, which we call the Temporal Noisy-Leaky Integrator (TNLI). The dynamic applications of the mo...
Chris Christodoulou, Guido Bugmann, Trevor G. Clar...
CVPR
2008
IEEE
14 years 7 months ago
Context and observation driven latent variable model for human pose estimation
Current approaches to pose estimation and tracking can be classified into two categories: generative and discriminative. While generative approaches can accurately determine human...
Abhinav Gupta, Trista Chen, Francine Chen, Don Kim...
EVENT
2001
267views more  EVENT 2001»
13 years 6 months ago
View-Invariant Representation and Learning of Human Action
Automatically understanding human actions from video sequences is a very challenging problem. This involves the extraction of relevant visual information from a video sequence, re...
Cen Rao, Mubarak Shah
WACV
2005
IEEE
13 years 11 months ago
Combining View-Based and Model-Based Tracking of Articulated Human Movements
Many existing systems for human body tracking are based on dynamic model-based tracking that is driven by local image features. Alternatively, within a view-based approach, tracki...
Cristóbal Curio, Martin A. Giese