Learning Gait Parameters for Locomotion in Virtual Reality Systems. Zhao, J. & Allison, R. S. In Wannous, H., Pala, P., Daoudi, M., & Flórez-Revuelta, F., editors, Understanding Human Activities Through 3D Sensors. UHA3DS 2016., volume 10188, of Lecture Notes in Computer Science, pages 59-73, 2018. ![Learning Gait Parameters for Locomotion in Virtual Reality Systems [link]](https://bibbase.org/img/filetypes/link.svg "link")
-1 doi abstract bibtex Mechanical repositioning is a locomotion technique that uses a mechanical device (i.e. locomotion interface), such as treadmills and pedaling devices, to cancel the displacement of a user for walking on the spot. This technique is especially useful for virtual reality (VR) systems that use large-scale projective displays for visualization. In this paper, we present a machine learning approach for developing a mechanical repositioning technique based on a 1-D treadmill for interacting with a unique new large-scale projective display, named as the Wide-Field Immersive Stereoscopic Environment (WISE). We also assessed the usability of the proposed approach through a novel user study that asked participants to pursue a rolling ball at variable speed in a virtual scene. Our results show that participants differ in their ability to carry out the task. We provide an explanation for the variable performance of the participants based on the locomotion technique.
@inproceedings{Zhao:2016ab,
abstract = {Mechanical repositioning is a locomotion technique that uses a mechanical device (i.e. locomotion interface), such as treadmills and pedaling devices, to cancel the displacement of a user for walking on the spot. This technique is especially useful for virtual reality (VR) systems that use large-scale projective displays for visualization. In this paper, we present a machine learning approach for developing a mechanical repositioning technique based on a 1-D treadmill for interacting with a unique new large-scale projective display, named as the Wide-Field Immersive Stereoscopic Environment (WISE). We also assessed the usability of the proposed approach through a novel user study that asked participants to pursue a rolling ball at variable speed in a virtual scene. Our results show that participants differ in their ability to carry out the task. We provide an explanation for the variable performance of the participants based on the locomotion technique.},
annote = {2nd International Workshop on Understanding Human Activities through 3D Sensors (UHA3DS'16)
Dec 4 , 2016, Mexico, Mexico},
author = {Zhao, J. and Allison, R. S.},
booktitle = {Understanding Human Activities Through 3D Sensors. UHA3DS 2016.},
date-added = {2016-12-04 21:58:08 +0000},
date-modified = {2018-05-25 00:29:53 +0000},
doi = {10.1007/978-3-319-91863-1_5},
editor = {Hazem Wannous and Pietro Pala and Mohamed Daoudi and Francisco Fl{\'o}rez-Revuelta},
keywords = {Optic flow & Self Motion (also Locomotion & Aviation)},
pages = {59-73},
series = {Lecture Notes in Computer Science},
title = {Learning Gait Parameters for Locomotion in Virtual Reality Systems},
url-1 = {https://doi.org/10.1007/978-3-319-91863-1_5},
volume = {10188},
year = {2018},
url-1 = {https://doi.org/10.1007/978-3-319-91863-1_5}}
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