Data-Driven Reconstruction of Human Locomotion Using a Single Smartphone
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Date
2014
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Publisher
The Eurographics Association and John Wiley and Sons Ltd.
Abstract
Generating a visually appealing human motion sequence using low-dimensional control signals is a major line of study in the motion research area in computer graphics. We propose a novel approach that allows us to reconstruct full body human locomotion using a single inertial sensing device, a smartphone. Smartphones are among the most widely used devices and incorporate inertial sensors such as an accelerometer and a gyroscope. To find a mapping between a full body pose and smartphone sensor data, we perform low dimensional embedding of full body motion capture data, based on a Gaussian Process Latent Variable Model. Our system ensures temporal coherence between the reconstructed poses by using a state decomposition model for automatic phase segmentation. Finally, application of the proposed nonlinear regression algorithm finds a proper mapping between the latent space and the sensor data. Our framework effectively reconstructs plausible 3D locomotion sequences. We compare the generated animation to ground truth data obtained using a commercial motion capture system.
Description
@article{10.1111:cgf.12469,
journal = {Computer Graphics Forum},
title = {{Data-Driven Reconstruction of Human Locomotion Using a Single Smartphone}},
author = {Eom, Haegwang and Choi, Byungkuk and Noh, Junyong},
year = {2014},
publisher = {The Eurographics Association and John Wiley and Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.12469}
}