Automatic Gesture Recognition for Health Care Using ReliefF and Fuzzy kNN View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2015

AUTHORS

Sriparna Saha , Monalisa Pal , Amit Konar , Diptendu Bhattacharya

ABSTRACT

This work describes a simple method to detect gestures revealing muscle and joint pain. The data is acquired using Kinect Sensor. For the purpose of feature extraction, the twenty joint coordinates are processed in three dimensional space. From each frame, 171 Euclidean distances are calculated and to reduce the dimension of the feature space, ReliefF algorithm is implemented. The classification stage is consists of fuzzy k-nearest neighbour classifier. The proposed method is employed to recognize 24 body gestures and yields a high recognition rate of 90.63 % which is comparatively higher than several other algorithms for young person gesture recognition works. More... »

PAGES

709-717

References to SciGraph publications

Book

TITLE

Information Systems Design and Intelligent Applications

ISBN

978-81-322-2246-0
978-81-322-2247-7

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-81-322-2247-7_72

DOI

http://dx.doi.org/10.1007/978-81-322-2247-7_72

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1033829255


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