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- W2038628849 abstract "This work proposes an identification system for smart buildings using footstep information. Basically, the system has three modules: pre-processing, feature extraction and selection, and classification of the information. Gait frequency, spectral envelope, cepstral and mel-cepstral analysis and loudness compose the set of parameters used to identify subjects in the smart building. In order to select features, the Fisher's criterion was used. For the classification task, K-Means and K-NN algorithms were performed along with different methodologies for test and validation. Moreover, the best sets were gathered, increasing the accuracy of classification. Several experiments were performed with 15 subjects wearing 6 different footwear. The classification rates were in the range from 33.5% to 97.5%." @default.
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- W2038628849 date "2010-07-01" @default.
- W2038628849 modified "2023-10-14" @default.
- W2038628849 title "Identification system for smart homes using footstep sounds" @default.
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- W2038628849 doi "https://doi.org/10.1109/isie.2010.5637551" @default.
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