Analysis of Gait Pattern to Recognize the Human Activities

Abstract

-Human activity recognition based on the computer vision is the process of labelling image sequences with action labels. Accurate systems for this problem are applied in areas such as visual surveillance, human computer interaction and video retrieval. The challenges are due to variations in motion, recording settings and gait differences. Here we propose an approach to recognize the human activities through gait. Activity recognition through Gait is the process of identifying an activity by the manner in which they walk. The identification of human activities in a video, such as a person is walking, running, jumping, jogging etc are important activities in video surveillance. We contribute the use of Model based approach for activity recognition with the help of movement of legs only. Experimental results suggest that our method are able to recognize the human activities with a good accuracy rate and robust to shadows present in the videos.

A Machine Learning Method with Threshold Based Parallel Feature Fusion and Feature Selection for Automated Gait Recognition

“…Ageneralgaitrecognitionframeworkconsistsofseveralsubstepssuchaspreprocessing,ROI detection,featureextractionandrecognition.Thepreprocessingstephasmuchimportanceforobtaining highrecognitionratebecausetherawinputvideoshaveacomplexbackgroundandlowcontrast.The lowcontrastvideosaffectROIdetectionwhichlaterondegradestherecognitionaccuracy.Therefore, preprocessingisamajorstepforimprovingthecontrastofinputvideoandalsoremovesextranoise suchaschangeinbackground,variationsandhumanchange.Ingaitrecognition,differentsegmentation methods have been introduced for ROI detection such as background subtraction, thresholding, watershed and few more (Piccardi, 2004;Gupta, Dixit et al, 2014). There are several types of featureswhichexistincomputervisionsuchastexture,color,geometric,shape,Gaborandwavelet transform.Thesefeaturesarehighinnumberofdimensions;therefore,theyreducetheaccuracy.This kindofproblemisresolvedbyseveralresearchersbytheimplementationofreductiontechniques.…”

IJIMAI Editor's Note - Vol. 2 Issue 7

“…Gupta et al [1] explores the use of analytics techniques towards the recognition of human activities (i.e. what a person is doing) using recorded videos as data source.…”

IJIMAI Editor's Note - Vol. 3 Issue 1

“…Fukuda et al [1] talks about bayesian network, which are regarded as one of the essential tools to analyze causal relationship between events from data. To learn the structure of highly-reliable Bayesian networks from data as quickly as possible is one of the important problems that several studies have been tried to achieve.…”