Abstract
We present a novel algorithm for automatically synthesizing personalized walking gaits for a human user from noisy motion caputre data. The overall approach is robust and can generate personalized gaits with little or no artistic intervention using commodity sensors.
Video
Paper
Generating Virtual Avatars with Personalized Walking Gaits using commodity hardware, ACM Multimedia 2017.
Sahil Narang, Andrew Best, Ari Shapiro, and Dinesh Manocha
@inproceedings{Narang:2017:GVA:3126686.3126766,
author = {Narang, Sahil and Best, Andrew and Shapiro, Ari and Manocha, Dinesh},
title = {Generating Virtual Avatars with Personalized Walking Gaits Using Commodity Hardware},
booktitle = {Proceedings of the on Thematic Workshops of ACM Multimedia 2017},
series = {Thematic Workshops '17},
year = {2017},
isbn = {978-1-4503-5416-5},
location = {Mountain View, California, USA},
pages = {219--227},
numpages = {9},
url = {http://doi.acm.org/10.1145/3126686.3126766},
doi = {10.1145/3126686.3126766},
acmid = {3126766},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {gait modeling, perception, virtual avatars},
}