Research On Algorithm Of Human Gait Recognition Based On Sparse Representation
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| Titre | Research On Algorithm Of Human Gait Recognition Based On Sparse Representation |
| Type de publication | Conference Paper |
| Year of Publication | 2016 |
| Auteurs | Guan Y.D, Zhu R.F, Feng J.Y, Du K., Zhang X.R |
| Conference Name | PROCEEDINGS OF 2016 SIXTH INTERNATIONAL CONFERENCE ON INSTRUMENTATION & MEASUREMENT, COMPUTER, COMMUNICATION AND CONTROL (IMCCC 2016) |
| Publisher | IEEE; IEEE Comp Soc; IEEE Instrumentat & Measurement Soc; IEEE Instrumentat & Measurement Soc, Beijing & Harbin Joint Chapter; Heilongjiang Instrument & Measurement Soc |
| Conference Location | 345 E 47TH ST, NEW YORK, NY 10017 USA |
| ISBN Number | 978-1-5090-1195-7 |
| Mots-clés | Gabor Wavelet feature, Gait Recognition, Local Binary Pattern, Shifted Energy Image, Sparse Represatation |
| Résumé | when the gait feature is recognized, it will be hard to meet the real-time need due to the complexity and long calculated time of the recognition algorithm. Under this circumstance, a novel sparse representation based human gait recognition method is put forth which is based on. First of all, human silhouette is established and gait period is calculated. Next, we adopt Shifting Energy Image (SEI) as the feature of image and then extract Gabor Wavelet and Local Binary Pattern features. Finally, gait feature will be classified and recognized by using sparse representation. CASIA B gait database will be used in the experiment with a view of 90 degrees. The result witnesses that this method has higher recognition rate and can meet the needs of real-time. |
| DOI | 10.1109/IMCCC.2016.71 |