Marker-Based and Marker-Less Motion Capturing Video Data: Person and Activity Identification Comparison Based on Machine Learning Approaches

Biomechanics is the study of physiological properties of data and the measurement of human behavior.In 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 tunes.One cannot perform any change in these inputs that make results reliable and increase the accuracy.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 patterns.In 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 algorithm.Also,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 algorithm.MBMCS 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.

Laser-induced damage tests based on a marker-based watershed algorithm with gray control

An effective damage test method based on a marker-based watershed algorithm with gray control(MWGC) is proposed to study the properties of damage induced by near-field laser irradiation for large-aperture laser facilities.Damage tests were performed on fused silica samples and information on the size of damage sites was obtained by this new algorithm,which can effectively suppress the issue of over-segmentation of images resulting from non-uniform illumination in darkfield imaging.Experimental analysis and results show that the lateral damage growth on the exit surface is exponential,and the number of damage sites decreases sharply with damage site size in the damage site distribution statistics.The average damage growth coefficients fitted according to the experimental results for Corning-7980 and Heraeus-Suprasil312 samples at 351 nm are 1.10 ± 0.31 and 0.60 ± 0.09,respectively.

Trajectory tracking control of robotic transcranial magnetic stimulation

Purpose–Transcranial magnetic stimulation(TMS)is a non-invasive brain stimulation technique.Based on the unique functions of TMS,it has been widely used in clinical,scientific research and other fields.Nowadays,the robot-assisted automatic TMS has become the trend.In order to simplify the operation procedures of robotic TMS and reduce the costs,the purpose of this paper is to apply the marker-based augmented-reality technology to robotic TMS system.Design/methodology/approach–By using the marker of ARToolKitPlus library and monocular camera,the patient’s head is positioned in real time.Furthermore,the force control is applied to keep contact between the coil and subject’s head.Findings–The authors fuse with visual positioning which is based on augmented-reality and force-control technologies to track the movements of the patient’s head,bring the coil closer to the stimulation site and increase treatment effects.Experimental results indicate that the trajectory tracking control of robotic TMS system designed in this paper is practical and flexible.Originality/value–This paper provides a trajectory tracking control method for the robotic TMS.The marker-based augmented-reality technology is implemented which simplifies the operation procedures of robotic TMS as well as reduce the costs.During the treatment process,the patients would wear an AR glasses,which can help patients relax through virtual scenes and reduce the uncomfortableness produce by treatment.