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Sensors 2017, 17(11), 2688; https://doi.org/10.3390/s17112688

A Similarity Analysis of Audio Signal to Develop a Human Activity Recognition Using Similarity Networks

1
Academic Unit of Electrical Engineering, Autonomous University of Zacatecas, Jardín Juarez 147, Centro, Zacatecas 98000, Zacatecas, Mexico
2
CONACyT—Academic Unit of Electrical Engineering, Autonomous University of Zacatecas , Jardín Juarez 147, Centro, Zacatecas 98000, Zacatecas, Mexico
3
Chemical Engineering Program, Autonomous University of Zacatecas, Ciudad Universitaria Siglo XXI, Carretera Zacatecas-Guadalajara Km. 6, Ejido La Escondida, Zacatecas 98160, Zacatecas, Mexico
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Received: 14 September 2017 / Revised: 1 November 2017 / Accepted: 16 November 2017 / Published: 21 November 2017
(This article belongs to the Section Sensor Networks)
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Abstract

Human Activity Recognition (HAR) is one of the main subjects of study in the areas of computer vision and machine learning due to the great benefits that can be achieved. Examples of the study areas are: health prevention, security and surveillance, automotive research, and many others. The proposed approaches are carried out using machine learning techniques and present good results. However, it is difficult to observe how the descriptors of human activities are grouped. In order to obtain a better understanding of the the behavior of descriptors, it is important to improve the abilities to recognize the human activities. This paper proposes a novel approach for the HAR based on acoustic data and similarity networks. In this approach, we were able to characterize the sound of the activities and identify those activities looking for similarity in the sound pattern. We evaluated the similarity of the sounds considering mainly two features: the sound location and the materials that were used. As a result, the materials are a good reference classifying the human activities compared with the location. View Full-Text
Keywords: human activity recognition; similarity networks; mel frequency cepstral coefficients human activity recognition; similarity networks; mel frequency cepstral coefficients
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García-Hernández, A.; Galván-Tejada, C.E.; Galván-Tejada, J.I.; Celaya-Padilla, J.M.; Gamboa-Rosales, H.; Velasco-Elizondo, P.; Cárdenas-Vargas, R. A Similarity Analysis of Audio Signal to Develop a Human Activity Recognition Using Similarity Networks. Sensors 2017, 17, 2688.

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