Human Gait Symmetry Assessment using a Depth Camera and Mirrors
Abstract
This paper proposes a reliable approach for human gait symmetry assessment using a depth camera and two mirrors. The input of our system is a sequence of 3D point clouds which are formed from a setup including a Time-of-Flight (ToF) depth camera and two mirrors. A cylindrical histogram is estimated for describing the posture in each point cloud. The sequence of such histograms is then separated into two sequences of sub-histograms representing two half-bodies. A cross-correlation technique is finally applied to provide values describing gait symmetry indices. The evaluation was performed on 9 different gait types to demonstrate the ability of our approach in assessing gait symmetry. A comparison between our system and related methods, that employ different input data types, is also provided.
- Publication:
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arXiv e-prints
- Pub Date:
- August 2019
- DOI:
- 10.48550/arXiv.1908.07422
- arXiv:
- arXiv:1908.07422
- Bibcode:
- 2019arXiv190807422N
- Keywords:
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- Computer Science - Computer Vision and Pattern Recognition
- E-Print:
- Computers in Biology and Medicine 101 (2018) 174-183