Training Classifiers with Shadow Features for Sensor-Based Human Activity Recognition

In this paper, a novel training/testing process for building/using a classification model based on human activity recognition (HAR) is proposed. Traditionally, HAR has been accomplished by a classifier that learns the activities of a person by training with skeletal data obtained from a motion senso...

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Detalles Bibliográficos
Autores principales: Fong, Simon, Song, Wei, Cho, Kyungeun, Wong, Raymond, Wong, Kelvin K. L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5375762/
https://www.ncbi.nlm.nih.gov/pubmed/28264470
http://dx.doi.org/10.3390/s17030476

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5375762/
https://www.ncbi.nlm.nih.gov/pubmed/28264470
http://dx.doi.org/10.3390/s17030476

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