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Person tracking association using multi-modal systems
Cita
Belmonte Hernández, Alberto 
ORCID: https://orcid.org/0000-0002-4009-2662, Solachidis, V., Theodoridis, T., Hernández Peñaloza, Gustavo Adolfo ORCID: https://orcid.org/0000-0003-2177-6185, Conti, Giuseppe ORCID: https://orcid.org/0000-0003-3813-3012, Vretos, N., Álvarez García, Federico ORCID: https://orcid.org/0000-0001-7400-9591 and Daras, P.
(2017).
Person tracking association using multi-modal systems.
En: "IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS 2017)", 29/08/2017 - 01/09/2017, Lecce, Italy. pp. 416-421.
https://doi.org/10.1109/AVSS.2017.8078529.
ORCID: https://orcid.org/0000-0002-4009-2662, Solachidis, V., Theodoridis, T., Hernández Peñaloza, Gustavo Adolfo ORCID: https://orcid.org/0000-0003-2177-6185, Conti, Giuseppe ORCID: https://orcid.org/0000-0003-3813-3012, Vretos, N., Álvarez García, Federico ORCID: https://orcid.org/0000-0001-7400-9591 and Daras, P.
(2017).
Person tracking association using multi-modal systems.
En: "IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS 2017)", 29/08/2017 - 01/09/2017, Lecce, Italy. pp. 416-421.
https://doi.org/10.1109/AVSS.2017.8078529.
Descripción
| Título: | Person tracking association using multi-modal systems |
|---|---|
| Autor/es: |
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| Tipo de Documento: | Ponencia en Congreso o Jornada (Artículo) |
| Título del Evento: | IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS 2017) |
| Fechas del Evento: | 29/08/2017 - 01/09/2017 |
| Lugar del Evento: | Lecce, Italy |
| Título del Libro: | IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS 2017) |
| Fecha: | 2017 |
| Materias: | |
| ODS: | |
| Escuela: | E.T.S.I. Telecomunicación (UPM) |
| Departamento: | Señales, Sistemas y Radiocomunicaciones |
| Licencias Creative Commons: | Reconocimiento - Sin obra derivada - No comercial |
Resumen
In this paper, a novel multi-modal method for person identification in indoor environments is presented. This ap- proach relies on matching the skeletons detected by a Kinect v2 device with wearable devices equipped with inertial sen- sors. Movement features such as yaw and pitch changes are employed to associate a particular Kinect skeleton to a person using the wearable. The entire process of sensor cal- ibration, feature extraction, synchronization and matching is detailed in this work. Six detection scenarios were de- fined to assess the proposed method. Experimental results have shown a high accuracy in the association process.
Proyectos asociados
Tipo
Código
Acrónimo
Responsable
Título
Horizonte 2020
ICT4LIFE
Sin especificar
Sin especificar
Sin especificar
Más información
| ID de Registro: | 50218 |
|---|---|
| Identificador DC: | https://oa.upm.es/50218/ |
| Identificador OAI: | oai:oa.upm.es:50218 |
| Identificador DOI: | 10.1109/AVSS.2017.8078529 |
| URL Oficial: | https://ieeexplore.ieee.org/document/8078529/ |
| Depositado por: | Memoria Investigacion |
| Depositado el: | 22 May 2018 15:09 |
| Ultima Modificación: | 22 May 2018 15:09 |
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