Reactive Hand Movements from Arm Kinematics and EMG Signals Based on Hierarchical Gaussian Process Dynamical Models

2020 ◽  
pp. 127-140
Author(s):  
Nick Taubert ◽  
Jesse St. Amand ◽  
Prerana Kumar ◽  
Leonardo Gizzi ◽  
Martin A. Giese
Keyword(s):  
Gaussian Process ◽  
Hand Movements ◽  
Dynamical Models ◽  
Arm Kinematics

Visualizing State of Time-Series Data by Supervised Gaussian Process Dynamical Models

2015 ◽  
Vol 19 (5) ◽  
pp. 688-696
Author(s):  
Nobuhiko Yamaguchi ◽  
Keyword(s):  
Time Series ◽  
Gaussian Process ◽  
Time Series Data ◽  
Series Data ◽  
Nonlinear Dimensionality Reduction ◽  
Probabilistic Representation ◽  
Dynamical Models ◽  
Motion Data ◽  
Dimensionality Reduction Technique ◽  
Representation Of Time

Gaussian Process Dynamical Models (GPDMs) constitute a nonlinear dimensionality reduction technique that provides a probabilistic representation of time series data in terms of Gaussian process priors. In this paper, we report a method based on GPDMs to visualize the states of time-series data. Conventional GPDMs are unsupervised, and therefore, even when the labels of data are available, it is not possible to use this information. To overcome the problem, we propose a supervised GPDM (S-GPDM) that utilizes both the data and their corresponding labels. We demonstrate experimentally that the S-GPDM can locate related motion data closer together than conventional GPDMs.

scholarly journals Gaussian process dynamical models over dual quaternions

2015 ◽  
Author(s):  
Muriel Lang ◽  
Martin Kleinsteuber ◽  
Oliver Dunkley ◽  
Sandra Hirche
Keyword(s):  
Gaussian Process ◽  
Dynamical Models ◽  
Dual Quaternions

scholarly journals Pedestrian Path, Pose, and Intention Prediction Through Gaussian Process Dynamical Models and Pedestrian Activity Recognition

2019 ◽  
Vol 20 (5) ◽  
pp. 1803-1814 ◽  
Author(s):  
Raul Quintero Minguez ◽  
Ignacio Parra Alonso ◽  
David Fernandez-Llorca ◽  
Miguel Angel Sotelo
Keyword(s):  
Gaussian Process ◽  
Activity Recognition ◽  
Dynamical Models
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