6533b85efe1ef96bd12bf2ea

RESEARCH PRODUCT

Gait Analysis Using Multiple Kinect Sensors

Marco MoranaGabriele Maida

subject

Kinectbusiness.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONContrast (statistics)User ProfilingGaitSet (abstract data type)ComputingMethodologies_PATTERNRECOGNITIONGait (human)Position (vector)Feature (computer vision)Gait analysisAmbient IntellicenceComputer visionArtificial intelligencebusiness

description

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.

10.1007/978-3-319-03992-3_12http://hdl.handle.net/10447/96134