Document Type
Conference Proceeding
Publication Date
12-2016
Abstract
We present the results of analyzing gait motion in first-person video taken from a commercially available wearable camera embedded in a pair of glasses. The video is analyzed with three different computer vision methods to extract motion vectors from different gait sequences from four individuals for comparison against a manually annotated ground truth dataset. Using a combination of signal processing and computer vision techniques, gait features are extracted to identify the walking pace of the individual wearing the camera as well as validated using the ground truth dataset. Our preliminary results indicate that the extraction of activity from the video in a controlled setting shows strong promise of being utilized in different activity monitoring applications such as in the eldercare environment, as well as for monitoring chronic healthcare conditions.
Repository Citation
Schneider, B.,
& Banerjee, T.
(2016). Preliminary Investigation of Walking Motion Using a Combination of Image and Signal Processing. .
https://corescholar.libraries.wright.edu/knoesis/1098
Included in
Bioinformatics Commons, Communication Technology and New Media Commons, Databases and Information Systems Commons, OS and Networks Commons, Science and Technology Studies Commons
Comments
Presented at the International Conference on Computational Science and Computational Intelligence, Las Vegas, NV, December 15-17, 2016.