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- W297611092 abstract "[ANGLES] In this document we present the study of acoustic gait recognition using large scale feature extraction and support vector machines. This work includes the presentation of the database recorded in two phases, with a total of 305 people walking in three different ways that took part in the recordings, the classifier that has been used for the investigation, namely Support Vector Machines, and a section of experiments and results presented after all the experiments have been carried out. In addition, there is a conclusion with a summary of the work and some ideas that could be fulfilled by researchers interested in the theme. A good people recognition has been achieved using this method, obtaining almost a 40% of correctly classified people walking in a normal way. However, the study has gone further trying also a gender and shoe type identification. Surprisingly, these results have proved to get a better classification, obtaining around a 70% of correctly classified people for the gender classification and around a 60% for the shoe type classification." @default.
- W297611092 created "2016-06-24" @default.
- W297611092 creator A5049435426 @default.
- W297611092 date "2012-08-01" @default.
- W297611092 modified "2023-09-27" @default.
- W297611092 title "Acoustic Gait Recognition Using Large Scale Feature Extraction and Support Vector Machines" @default.
- W297611092 hasPublicationYear "2012" @default.
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