Imperial College London
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DrBennyLo

Faculty of Medicine, Department of Metabolism, Digestion and Reproduction

Visiting Reader
 
 
 
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Contact

 

+44 (0)20 7594 0806benny.lo Website

 
 
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Location

 

Bessemer BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Gu:2018:10.1109/BSN.2018.8329654,
author = {Gu, X and Deligianni, F and Lo, B and Chen, W and Yang, GZ},
doi = {10.1109/BSN.2018.8329654},
pages = {42--45},
title = {Markerless gait analysis based on a single RGB camera},
url = {http://dx.doi.org/10.1109/BSN.2018.8329654},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - Gait analysis is an important tool for monitoring and preventing injuries as well as to quantify functional decline in neurological diseases and elderly people. In most cases, it is more meaningful to monitor patients in natural living environments with low-end equipment such as cameras and wearable sensors. However, inertial sensors cannot provide enough details on angular dynamics. This paper presents a method that uses a single RGB camera to track the 2D joint coordinates with state-of-the-art vision algorithms. Reconstruction of the 3D trajectories uses sparse representation of an active shape model. Subsequently, we extract gait features and validate our results in comparison with a state-of-the-art commercial multi-camera tracking system. Our results are comparable to those from the current literature based on depth cameras and optical markers to extract gait characteristics.
AU  - Gu,X
AU  - Deligianni,F
AU  - Lo,B
AU  - Chen,W
AU  - Yang,GZ
DO  - 10.1109/BSN.2018.8329654
EP  - 45
PY  - 2018///
SP  - 42
TI  - Markerless gait analysis based on a single RGB camera
UR  - http://dx.doi.org/10.1109/BSN.2018.8329654
UR  - http://hdl.handle.net/10044/1/56158
ER  -
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