Comparison of Marker-Based and Marker-Less Systems for Low-Cost Human Motion Capture

2013 ◽  
Author(s):  
Sajeev C. Puthenveetil ◽  
Chinmay P. Daphalapurkar ◽  
Wenjuan Zhu ◽  
Ming C. Leu ◽  
Xiaoqing F. Liu ◽  
...  
Keyword(s):  
Motion Capture ◽  
Motion Tracking ◽  
Low Cost ◽  
Human Motion ◽  
Motion Data ◽  
Aircraft Fuselage ◽  
Modeling Software ◽  
Human Motion Simulation ◽  
Optical Motion ◽  
Quality Of Motion

To generate graphic simulation of human motion, marker-based optical motion capture technology is widely used because of the accuracy and reliability of motion data provided by this technology. However, tracking of human motion without markers is very desirable on the factory floor because the human operator does not need to wear a special suit mounted with markers and there is no physical interference with the manufacturing or assembly operation during the motion tracking. In this paper, we compare marker-based and marker-less motion capture systems. First, the operational principles of these two different types of systems are compared. Then the quality of motion data obtained by a marker-less system using Kinect is compared with that obtained by a marker-based system using Optitrack cameras. The comparison also includes the accuracy of body joint angles and variations in body segment lengths measured by the two different systems. Furthermore, we compare the human motion simulation developed in the Jack digital human modeling software using the data captured by these two systems when a person is performing a fastening operation on a physical mockup of the belly section of an aircraft fuselage.

Motion Capture of Fastening Operation Using Wiimotes for Ergonomic Analysis

2012 ◽  
Author(s):  
W. Zhu ◽  
C. P. Daphalapurkar ◽  
S. Chirayil Puthenveetil ◽  
M. C. Leu ◽  
X. F. Liu ◽  
...  
Keyword(s):  
Motion Capture ◽  
Vision System ◽  
Low Cost ◽  
Motion Capture System ◽  
Digital Human Modeling ◽  
Motion Data ◽  
Aircraft Fuselage ◽  
Modeling Software ◽  
Ergonomic Analysis ◽  
Digital Human

This paper presents an application of a Wii Remote (Wiimote) based, low-cost motion capture system for digital human simulation and ergonomic analysis of a fastening operation. The system includes a low-cost infrared (IR) based motion capture system developed using Wiimotes. A portable stereo vision system was used to capture the operator’s movements while performing a fastening operation during the assembly of an aircraft fuselage on the factory floor. IR LEDs mounted on the worker’s body served as markers. The captured motion data was used to generate a simulation of the operator’s arm movements and to perform ergonomic analysis with the help of digital human modeling software, Siemens Jack.

Gait Analysis in the Assessment of Patients Undergoing a Total Hip Replacement

2019 ◽  
Author(s):  
Daniele Regazzoni ◽  
Andrea Vitali ◽  
Filippo Colombo Zefinetti ◽  
Caterina Rizzi
Keyword(s):  
Motion Capture ◽  
Hip Replacement ◽  
Motion Tracking ◽  
Low Cost ◽  
Quantitative Measure ◽  
Clinical Information ◽  
Human Motion ◽  
Technical Solution ◽  
Specific Context ◽  
Main Challenge

Abstract Nowadays, healthcare centers are not familiar with quantitative approaches for patients’ gait evaluation. There is a clear need for methods to obtain objective figures characterizing patients’ performance. Actually, there are no diffused methods for comparing the pre- and post-operative conditions of the same patient, integrating clinical information and representing a measure of the efficiency of functional recovery, especially in the short-term distance of the surgical intervention. To this aim, human motion tracking for medical analysis is creating new frontiers for potential clinical and home applications. Motion Capture (Mocap) systems are used to allow detecting and tracking human body movements, such as gait or any other gesture or posture in a specific context. In particular, low-cost portable systems can be adopted for the tracking of patients’ movements. The pipeline going from tracking the scene to the creation of performance scores and indicators has its main challenge in the data elaboration, which depends on the specific context and to the detailed performance to be evaluated. The main objective of this research is to investigate whether the evaluation of the patient’s gait through markerless optical motion capture technology can be added to clinical evaluations scores and if it is able to provide a quantitative measure of recovery in the short postoperative period. A system has been conceived, including commercial sensors and a way to elaborate data captured according to caregivers’ requirements. This allows transforming the real gait of a patient right before and/or after the surgical procedure into a set of scores of medical relevance for his/her evaluation. The technical solution developed in this research will be the base for a large acquisition and data elaboration campaign performed in collaboration with an orthopedic team of surgeons specialized in hip arthroplasty. This will also allow assessing and comparing the short run results obtained by adopting different state-of-the-art surgical approach for the hip replacement.

Human Arm Motion Tracking by Orientation-Based Fusion of Inertial Sensors and Kinect Using Unscented Kalman Filter

2016 ◽  
Vol 138 (9) ◽  
Author(s):  
Arash Atrsaei ◽  
Hassan Salarieh ◽  
Aria Alasty
Keyword(s):  
Kalman Filter ◽  
Motion Capture ◽  
Motion Tracking ◽  
Inertial Sensors ◽  
Unscented Kalman Filter ◽  
Low Cost ◽  
Human Motion ◽  
Home Based ◽  
Human Arm ◽  
Arm Motion

Due to various applications of human motion capture techniques, developing low-cost methods that would be applicable in nonlaboratory environments is under consideration. MEMS inertial sensors and Kinect are two low-cost devices that can be utilized in home-based motion capture systems, e.g., home-based rehabilitation. In this work, an unscented Kalman filter approach was developed based on the complementary properties of Kinect and the inertial sensors to fuse the orientation data of these two devices for human arm motion tracking during both stationary shoulder joint position and human body movement. A new measurement model of the fusion algorithm was obtained that can compensate for the inertial sensors drift problem in high dynamic motions and also joints occlusion in Kinect. The efficiency of the proposed algorithm was evaluated by an optical motion tracker system. The errors were reduced by almost 50% compared to cases when either inertial sensor or Kinect measurements were utilized.

scholarly journals Application Of Motion Capture Systems In Ergonomic Analysis

2020 ◽  
Vol 1 (1) ◽  
pp. 107-117
Author(s):  
Tigran Petrosyan ◽  
Arayik Dunoyan ◽  
Hasmik Mkrtchyan
Keyword(s):  
Motion Capture ◽  
Motion Tracking ◽  
Low Cost ◽  
Objective Assessment ◽  
Body Motion ◽  
Optical Systems ◽  
Wide Range ◽  
Optical Motion ◽  
Set Up ◽  
Ergonomic Analysis

Currently different methods are used for ergonomic assessment and analysis. This review tries to show how motion capture technology is applied in the process of ergonomic assessment. The goals of the analysis were to identify the most adequate method for objective assessment of ergonomics. The results show that the optical motion tracking systems with special software can be used to perform digital analysis of body motion. These systems do not require long set up time, majority of them are portable and the sensors are available in the market for a low cost. Movements of the working person are captured without special clothes equipped with markers. Though the optical systems could be acceptable in a wide range of tasks, they have certain limitations in ergonomic analysis. The performance of optical systems depends on a number of variables such as lighting, type of movements, distance from the object and environmental artefacts. The performance of existing systems is not yet completely reliable, but the technology is on the path of improving its accuracy. There are also other mechanical and magnetic technologies used for ergonomic analysis. This review shows that ergonomic simulations using the motion capture technology significantly improves the quality of ergonomic analysis.

Research on Intangible Cultural Heritage Based on Motion Capture

2014 ◽  
Vol 568-570 ◽  
pp. 676-680
Author(s):  
Si Xi Chen ◽  
Shu Chen
Keyword(s):  
Cultural Heritage ◽  
Motion Capture ◽  
Low Cost ◽  
Three Dimensional ◽  
Intangible Cultural Heritage ◽  
Three Dimensional Model ◽  
Motion Data ◽  
Optical Motion ◽  
Capture Method ◽  
Optical Motion Capture

The application of digital technology on the protection of intangible cultural heritage is a major topic of research in recent years. The motion capture technology of protection will gradually replace the traditional recording methods such as texts, pictures and videos. It is valuable to build a high-fidelity, high-modular and low-cost digital platform for choreographic data collection and extended application. This paper studies the intangible cultural heritage of Quanzhou breast-clapping dance, one of the most famous choreographic intangible cultural heritages from China with standard optical motion capture method. The data are acquiring and processing after the dance motion capture, we binds the motion data and three-dimensional model using Motion Builder and build digital demonstration platform base on an OGRE engine to display the movements. The viewer can view at any angle and distance. The system can be easily applied in motion intangible cultural heritages protection project. Furthermore, the system can be provided versatile motion data for additional use.

scholarly journals Metrological Evaluation of Human–Robot Collaborative Environments Based on Optical Motion Capture Systems

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3748
Author(s):  
Leticia González ◽  
Juan C. Álvarez ◽  
Antonio M. López ◽  
Diego Álvarez
Keyword(s):  
Motion Capture ◽  
Motion Tracking ◽  
Industrial Robot ◽  
Human Motion ◽  
Factors Affecting ◽  
Collaborative Environment ◽  
Accuracy And Precision ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Metrological Evaluation

In the context of human–robot collaborative shared environments, there has been an increase in the use of optical motion capture (OMC) systems for human motion tracking. The accuracy and precision of OMC technology need to be assessed in order to ensure safe human–robot interactions, but the accuracy specifications provided by manufacturers are easily influenced by various factors affecting the measurements. This article describes a new methodology for the metrological evaluation of a human–robot collaborative environment based on optical motion capture (OMC) systems. Inspired by the ASTM E3064 test guide, and taking advantage of an existing industrial robot in the production cell, the system is evaluated for mean error, error spread, and repeatability. A detailed statistical study of the error distribution across the capture area is carried out, supported by a Mann–Whitney U-test for median comparisons. Based on the results, optimal capture areas for the use of the capture system are suggested. The results of the proposed method show that the metrological characteristics obtained are compatible and comparable in quality to other methods that do not require the intervention of an industrial robot.

scholarly journals Use of Human Motion Data to Train Wearable Robots

2021 ◽  
Vol 12 (6) ◽  
pp. 807-811
Author(s):  
JIBUM JUNG Et.al
Keyword(s):  
Motion Capture ◽  
Human Motion ◽  
Machine Learning Algorithms ◽  
Walking Robots ◽  
Motion Capture System ◽  
Motion Data ◽  
Wearable Robots ◽  
Human Movements ◽  
Optical Motion ◽  
Optical Motion Capture

Development of wearable robots is accelerating. Walking robots mimic human behavior and must operate without accidents. Human motion data are needed to train these robots. We developed a system for extracting human motion data and displaying them graphically.We extracted motion data using a Perception Neuron motion capture system and used the Unity engine for the simulation. Several experiments were performed to demonstrate the accuracy of the extracted motion data.Of the various methods used to collect human motion data, markerless motion capture is highly inaccurate, while optical motion capture is very expensive, requiring several high-resolution cameras and a large number of markers. Motion capture using a magnetic field sensor is subject to environmental interference. Therefore, we used an inertial motion capture system. Each movement sequence involved four and was repeated 10 times. The data were stored and standardized. The motions of three individuals were compared to those of a reference person; the similarity exceeded 90% in all cases. Our rehabilitation robot accurately simulated human movements: individually tailored wearable robots could be designed based on our data. Safe and stable robot operation can be verified in advance via simulation. Walking stability can be increased using walking robots trained via machine learning algorithms.

scholarly journals Precision, repeatability and accuracy of Optotrak® optical motion tracking systems

2016 ◽  
Author(s):  
Jill Schmidt ◽  
Devin R. Berg
Keyword(s):  
Rigid Body ◽  
Motion Tracking ◽  
Surgical Navigation ◽  
Plane Motion ◽  
Human Motion ◽  
Tracking Systems ◽  
Total Displacement ◽  
Camera Systems ◽  
Optical Motion ◽  
Optical Motion Tracking

In the field of biomechanics, optical motion tracking systems are commonly used to record human motion and assist in surgical navigation. Recently, motion tracking systems have been used to track implant and bone motion on a micron-level. The present study evaluated four different Optotrak® motion tracking systems to determine the precision, repeatability and accuracy under static testing conditions. The distance between the camera systems and the rigid body, as well as the tilt angle of the rigid body, did affect the resulting precision, repeatability and accuracy of the camera systems. The precision and repeatability, calculated as the within-trial and between-trial standard deviations, respectively, were less than 30 µm; with some configurations producing precision and repeatability less than 1 µm. The accuracy was less than 0.53% of the total displacement for the in-plane motion and less than 1.56% of the total displacement for the out-of-plane motion.

scholarly journals Gap Reconstruction in Optical Motion Capture Sequences Using Neural Networks

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6115
Author(s):  
Przemysław Skurowski ◽  
Magdalena Pawlyta
Keyword(s):  
Neural Networks ◽  
Motion Capture ◽  
Matrix Completion ◽  
Input Sequence ◽  
Feedforward Neural Networks ◽  
Network Architectures ◽  
Motion Data ◽  
Optical Motion ◽  
Body Kinematic ◽  
Optical Motion Capture

Optical motion capture is a mature contemporary technique for the acquisition of motion data; alas, it is non-error-free. Due to technical limitations and occlusions of markers, gaps might occur in such recordings. The article reviews various neural network architectures applied to the gap-filling problem in motion capture sequences within the FBM framework providing a representation of body kinematic structure. The results are compared with interpolation and matrix completion methods. We found out that, for longer sequences, simple linear feedforward neural networks can outperform the other, sophisticated architectures, but these outcomes might be affected by the small amount of data availabe for training. We were also able to identify that the acceleration and monotonicity of input sequence are the parameters that have a notable impact on the obtained results.

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