Gait Analysis Using Multiple Kinect Sensors

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A gait analysis technique to model user presences in an office scenario is presented in this chapter. In contrast with other approaches, we use unobtrusive sensors, i.e., an array of Kinect devices, to detect some features of interest. In particular, the position and the spatio-temporal evolution of some skeletal joints are used to define a set of gait features, which can be either static (e.g., person height) or dynamic (e.g., gait cycle duration). Data captured by multiple Kinects is merged to detect dynamic features in a longer walk sequence. The approach proposed here was been evaluated by using three classifiers (SVM, KNN, Naive Bayes) on different feature subsets.
Lingua originaleEnglish
Titolo della pubblicazione ospiteAdvances onto the Internet of Things How Ontologies Make the Internet of Things Meaningful
Numero di pagine11
Stato di pubblicazionePublished - 2014

Serie di pubblicazioni


All Science Journal Classification (ASJC) codes

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  • ???subjectarea.asjc.1700.1700???


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