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marker-Based and marker-less motion capturing Video Data: Person and Activity Identification Comparison Based on Machine Learning Approaches

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Computers, Materials & Continua 2021年第2期66卷 1269-1282页

作者： Syeda Binish Zahra Muhammad Adnan Khan Sagheer Abbas Khalid Masood Khan Mohammed A.Al-Ghamdi Sultan H.Almotiri School of Computer Science National College for Business Administration and EconomicsLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54792Pakistan Computer Science Department Umm Al-Qura UniversityMakkah CitySaudi Arabia

Biomechanics is the study of physiological properties of data and the measurement of human *** normal conditions,behavioural properties in stable form are created using various inputs of subconscious/conscious human activities such as speech style,body movements in walking patterns,writing style and voice *** cannot perform any change in these inputs that make results reliable and increase the *** aim of our study is to perform a comparative analysis between the marker-based motion capturing system(MBMCS)and the marker-less motion capturing system(MLMCS)using the lower body joint angles of human gait *** both the MLMCS and MBMCS,we collected trajectories of all the participants and performed joint angle computation to identify a person and recognize an activity(walk and running).Using five state of the art machine learning algorithms,we obtained 44.6%and 64.3%accuracy in person identification using MBMCS and MLMCS respectively with an ensemble algorithm(two angles as features).In the second set of experiments,we used six machine learning algorithms to obtain 65.9%accuracy with the k-nearest neighbor(KNN)algorithm(two angles as features)and 74.6%accuracy with an ensemble ***,by increasing features(6 angles),we obtained higher accuracy of 99.3%in MBMCS for person recognition and 98.1%accuracy in MBMCS for activity recognition using the KNN *** is computationally expensive and if we redesign the model of OpenPose with more body joint points and employ more features,MLMCS(low-cost system)can be an effective approach for video data analysis in a person identification and activity recognition process.

关键词： marker-based motion capturing system marker-less motion capturing system support vector machine K-nearest neighbor

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