Publication Type:

Conference Proceedings

Source:

Proceedings - 2012 International Conference on Advances in Computing and Communications, ICACC 2012, Cochin, p.31-34 (2012)

ISBN:

9780769547237

URL:

http://www.scopus.com/inward/record.url?eid=2-s2.0-84867938963&partnerID=40&md5=f2fe4487c2ba9045178ae97a185126be

Keywords:

Daily lives, Decision trees, Gait, Gait analysis, Gait recognition, Human gait, Human identification, Image processing, Joint angle, Keypose, Medical fields, Shapelets, Silhouette, Silhouette images, Time series, Time-series data

Abstract:

<p>Human gait is the main activity of daily life. Gait can be used for applications like human identification (in medical field etc). Since gait can be perceived from a distance it can be used for human identification. Gait recognition means identifying the person with his/her gait. Human identification using gait can be used in surveillance. A method is proposed for gait recognition using a technique which uses time series shapelets. First, for a gait video a preprocessing is done to extract the silhouette images from the video. From these silhouette images features like joint angle and swing distance are extracted which can be represented as the time series data. From this time series data, time series shapelets are extracted. Shapelets are subsequence of time series data which can discriminate between classes. Shapelets are maximally representative of the class. These time series shapelets can be used to identify human by their gait. Shapelets can also be used for classification. After extracting the shapelets, the prediction is done using the decision tree. In that it can be used for classifying normal and abnormal human gait. © 2012 IEEE.</p>

Notes:

cited By (since 1996)0; Conference of org.apache.xalan.xsltc.dom.DOMAdapter@58e76980 ; Conference Date: org.apache.xalan.xsltc.dom.DOMAdapter@40bf8019 Through org.apache.xalan.xsltc.dom.DOMAdapter@5c730a84; Conference Code:93547

Cite this Research Publication

T. Shajina and Dr. Bhagavathi Sivakumar P., “Human gait recognition and classification using time series Shapelets”, Proceedings - 2012 International Conference on Advances in Computing and Communications, ICACC 2012. Cochin, pp. 31-34, 2012.

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