An Empirical Study for Human Behavior Analysis

Thispaperpresentsanempiricalstudyforhumanbehavioranalysisbasedonthreedistinctfeature extractiontechniques:HistogramsofOrientedGradients(HOG),LocalBinaryPattern(LBP)and ScaleInvariantLocalTernaryPattern(SILTP).Theutilisedpublicvideosrepresentingspatio-temporal problemareaof investigation includeINRIApersondetectionandWeizmannpedestrianactivity datasets.ForINRIAdataset,bothLBPandHOGwereabletoeliminateredundantvideodataand showhuman-intelligiblefeaturevisualisationofextractedfeaturesrequiredforclassificationtasks. However,forWeizmanndatasetonlyHOGfeatureextractionwasfoundtoworkwellwithclassifying fiveselectedactivities/exercises(walking,running,skipping,jumpingandjacking). KEywoRDS Histograms of Oriented Gradients (HOG), Human Behavior Recognition, Local Binary Pattern (LBP)

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