Md Wasiur Rahman, M. Gavrilova
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引用次数: 2
Human Identification Using Gait Skeletal Joint Distance Features
Gaitnotonlydefinesthewayapersonwalks,butalsoprovidesinsightsonanindividual’sdaily routine,mentalstateorevencognitivefunction.Theimportanceofincorporatingcognitivebehavior andanalysisinbiometricsystemshasbeennotedrecently.Inthisarticle,authorsdevelopabiometric securitysystemusinggait-basedskeletalinformationobtainedfromMicrosoftKinectv1sensor.The gaitcycleiscalculatedbydetectingthethreeconsecutivelocalminimabetweenthejointdistance ofleftandrightankles.Authorshaveutilizedthedistancefeaturevectorforeachofthejointswith respecttootherjointsinthegaitcycle.Aftermeanandvariancefeaturesareextractedfromthedistance featurevector,theKNNalgorithmisusedforclassificationpurpose.Theclassificationaccuracyofthe authors’approachis93.33%.Experimentalresultsshowthattheproposedapproachachievesbetter recognitionaccuracythenotherstate-of-the-artapproaches.Incorporatinggaitbiometricinasituation awarenesssystemforidentificationofamentalstateisoneofthefuturedirectionsofthisresearch. KeywoRDS Biometric System, Cognitive Function, Feature Distance Vector, Gait, Gait Cycle, K Nearest Neighbors (KNN), Kinect Sensor, Pattern Recognition
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