Human Motion Capture Driven by Orientation Measurements

1999 ◽  
Vol 8 (2) ◽  
pp. 187-203 ◽  
Author(s):  
Tom Molet ◽  
Ronan Boulic ◽  
Daniel Thalmann
Keyword(s):  
Motion Capture ◽  
Human Motion ◽  
High Rate ◽  
Position Measurement ◽  
Human Motion Capture ◽  
Fast Tracking ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Tracking Object ◽  
Capture Techniques

Motion-capture techniques are rarely based on orientation measurements for two main reasons: (1) optical motion-capture systems are designed for tracking object position rather than their orientation (which can be deduced from several trackers), (2) known animation techniques, like inverse kinematics or geometric algorithms, require position targets constantly, but orientation inputs only occasionally. We propose a complete human motion-capture technique based essentially on orientation measurements. The position measurement is used only for recovering the global position of the performer. This method allows fast tracking of human gestures for interactive applications as well as high rate recording. Several motion-capture optimizations, including the multijoint technique, improve the posture realism. This work is well suited for magnetic-based systems that rely more on orientation registration (in our environment) than position measurements that necessitate difficult system calibration.

scholarly journals Optical motion capture dataset of selected techniques in beginner and advanced Kyokushin karate athletes

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Agnieszka Szczęsna ◽  
Monika Błaszczyszyn ◽  
Magdalena Pawlyta
Keyword(s):  
Motion Capture ◽  
Three Dimensional ◽  
Data File ◽  
Human Motion ◽  
Skill Levels ◽  
Human Motion Capture ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Capture Techniques ◽  
Karate Athletes

AbstractHuman motion capture is commonly used in various fields, including sport, to analyze, understand, and synthesize kinematic and kinetic data. Specialized computer vision and marker-based optical motion capture techniques constitute the gold-standard for accurate and robust human motion capture. The dataset presented consists of recordings of 37 Kyokushin karate athletes of different ages (children, young people, and adults) and skill levels (from 4th dan to 9th kyu) executing the following techniques: reverse lunge punch (Gyaku-Zuki), front kick (Mae-Geri), roundhouse kick (Mawashi-Geri), and spinning back kick (Ushiro-Mawashi-Geri). Each technique was performed approximately three times per recording (i.e., to create a single data file), and under three conditions where participants kicked or punched (i) in the air, (ii) a training shield, or (iii) an opponent. Each participant undertook a minimum of two trials per condition. The data presented was captured using a Vicon optical motion capture system with Plug-In Gait software. Three dimensional trajectories of 39 reflective markers were recorded. The resultant dataset contains a total of 1,411 recordings, with 3,229 single kicks and punches. The recordings are available in C3D file format. The dataset provides the opportunity for kinematic analysis of different combat sport techniques in attacking and defensive situations.

Research of Maintainability Evaluation for Civil Aircrafts Based on the Motion Capture System

2012 ◽  
Vol 198-199 ◽  
pp. 1062-1066
Author(s):  
Xu Dong Wu ◽  
Hu Liu ◽  
Song Mo ◽  
Zhe Wu ◽  
Ying Li
Keyword(s):  
Motion Capture ◽  
Human Motion ◽  
Test Case ◽  
Motion Capture System ◽  
Promising Technique ◽  
Human Motion Capture ◽  
Civil Aircraft ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Design Attribute

Maintainability is a main design attribute of a civil airplane. So evaluation to the maintainability is very important for the design of the civil aircraft. The Human motion capture is a promising technique for maintainability evaluation. In this article, a method about the maintainability evaluation based on the optical motion capture system was presented. Then a test case was developed to demonstrate the feasibility of the method. The test case mainly focused on the accessibility of the civil aircraft.

scholarly journals Measuring Spinal Mobility Using an Inertial Measurement Unit System: A Validation Study in Axial Spondyloarthritis

Diagnostics ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 426
Author(s):  
I. Concepción Aranda-Valera ◽  
Antonio Cuesta-Vargas ◽  
Juan L. Garrido-Castro ◽  
Philip V. Gardiner ◽  
Clementina López-Medina ◽  
...  
Keyword(s):  
Outcome Measures ◽  
Motion Capture ◽  
Axial Spondyloarthritis ◽  
Human Motion ◽  
Spinal Mobility ◽  
Measurement Unit ◽  
Human Motion Analysis ◽  
Inertial Measurement ◽  
Optical Motion ◽  
Optical Motion Capture

Portable inertial measurement units (IMUs) are beginning to be used in human motion analysis. These devices can be useful for the evaluation of spinal mobility in individuals with axial spondyloarthritis (axSpA). The objectives of this study were to assess (a) concurrent criterion validity in individuals with axSpA by comparing spinal mobility measured by an IMU sensor-based system vs. optical motion capture as the reference standard; (b) discriminant validity comparing mobility with healthy volunteers; (c) construct validity by comparing mobility results with relevant outcome measures. A total of 70 participants with axSpA and 20 healthy controls were included. Individuals with axSpA completed function and activity questionnaires, and their mobility was measured using conventional metrology for axSpA, an optical motion capture system, and an IMU sensor-based system. The UCOASMI, a metrology index based on measures obtained by motion capture, and the IUCOASMI, the same index using IMU measures, were also calculated. Descriptive and inferential analyses were conducted to show the relationships between outcome measures. There was excellent agreement (ICC > 0.90) between both systems and a significant correlation between the IUCOASMI and conventional metrology (r = 0.91), activity (r = 0.40), function (r = 0.62), quality of life (r = 0.55) and structural change (r = 0.76). This study demonstrates the validity of an IMU system to evaluate spinal mobility in axSpA. These systems are more feasible than optical motion capture systems, and they could be useful in clinical practice.

Riding Motion Capture System Using Inertial Measurement Units with Contact Constraints

2019 ◽  
Vol 13 (4) ◽  
pp. 506-516 ◽  
Author(s):  
Tsubasa Maruyama ◽  
Mitsunori Tada ◽  
Haruki Toda ◽  
◽  
Keyword(s):  
Motion Capture ◽  
Bicycle Ergometer ◽  
Human Motion ◽  
Position Estimation ◽  
Estimation Accuracy ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Outdoor Environments ◽  
Optical Motion ◽  
Optical Motion Capture

The measurement of human motion is an important aspect of ergonomic mobility design, in which the mobility product is evaluated based on human factors obtained by digital human (DH) technologies. The optical motion-capture (MoCap) system has been widely used for measuring human motion in laboratories. However, it is generally difficult to measure human motion using mobility products in real-world scenarios, e.g., riding a bicycle on an outdoor slope, owing to unstable lighting conditions and camera arrangements. On the other hand, the inertial-measurement-unit (IMU)-based MoCap system does not require any optical devices, providing the potential for measuring riding motion even in outdoor environments. However, in general, the estimated motion is not necessarily accurate as there are many errors due to the nature of the IMU itself, such as drift and calibration errors. Thus, it is infeasible to apply the IMU-based system to riding motion estimation. In this study, we develop a new riding MoCap system using IMUs. The proposed system estimates product and human riding motions by combining the IMU orientation with contact constraints between the product and DH, e.g., DH hands in contact with handles. The proposed system is demonstrated with a bicycle ergometer, including the handles, seat, backrest, and foot pedals, as in general mobility products. The proposed system is further validated by comparing the estimated joint angles and positions with those of the optical MoCap for three different subjects. The experiment reveals both the effectiveness and limitations of the proposed system. It is confirmed that the proposed system improves the joint position estimation accuracy compared with a system using only IMUs. The angle estimation accuracy is also improved for near joints. However, it is observed that the angle accuracy decreases for a few joints. This is explained by the fact that the proposed system modifies the orientations of all body segments to satisfy the contact constraints, even if the orientations of a few joints are correct. This further confirms that the elapsed time using the proposed system is sufficient for real-time application.

Data compensation based on the additional feature information for collaborative interactive operation with optical human motion capture system

2018 ◽  
Vol 09 (06) ◽  
pp. 1850060
Author(s):  
Xiangyang Li ◽  
Rui Wang ◽  
Zhe Xu ◽  
Lei Pan ◽  
Zhili Zhang
Keyword(s):  
Motion Capture ◽  
Human Motion ◽  
Practical Implementation ◽  
Body Parts ◽  
Motion Capture System ◽  
Human Motion Capture ◽  
Interactive Operation ◽  
Optical Motion ◽  
Feature Information ◽  
Infrared Cameras

As the effective capture region of optical motion capture system is limited by quantity, installation mode, resolution and focus of infrared cameras, the reflective markers on certain body parts (such as wrists, elbows, etc.) of multi-actual trainees may be obscured when they perform the collaborative interactive operation. To address this issue, motion data compensation method based on the additional feature information provided by the electromagnetic spatial position tracking equipment is proposed in this paper. The main working principle and detailed realization process of the proposed method are introduced step by step, and the practical implementation is presented to illustrate its validity and efficiency. The results show that the missing capture data and motion information of relevant obscured markers on arms can be retrieved with the proposed method, which can avoid the simulation motions of corresponding virtual operators being interrupted and deformed during the collaborative interactive operation process performed by multi-actual trainees with optical human motion capture system in a limited capture range.

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 Foot Position Measurement during Assistive Motion for Sit-to-Stand Using a Single Inertial Sensor and Shoe-Type Force Sensors

2021 ◽  
Vol 18 (19) ◽  
pp. 10481
Author(s):  
Kodai Kitagawa ◽  
Ibai Gorordo Fernandez ◽  
Takayuki Nagasaki ◽  
Sota Nakano ◽  
Mitsumasa Hida ◽  
...  
Keyword(s):  
Motion Capture ◽  
Inertial Sensor ◽  
Body Height ◽  
Force Sensors ◽  
Motion Capture System ◽  
Position Measurement ◽  
Sit To Stand ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Foot Position

Assistive motion for sit-to-stand causes lower back pain (LBP) among caregivers. Considering previous studies that showed that foot position adjustment could reduce lumbar load during assistive motion for sit-to-stand, quantitative monitoring of and instructions on foot position could contribute toward reducing LBP among caregivers. The present study proposes and evaluates a new method for the quantitative measurement of foot position during assistive motion for sit-to-stand using a few wearable sensors that are not limited to the measurement area. The proposed method measures quantitative foot position (anteroposterior and mediolateral distance between both feet) through a machine learning technique using features obtained from only a single inertial sensor on the trunk and shoe-type force sensors. During the experiment, the accuracy of the proposed method was investigated by comparing the obtained values with those from an optical motion capture system. The results showed that the proposed method produced only minor errors (less than 6.5% of body height) when measuring foot position during assistive motion for sit-to-stand. Furthermore, Bland–Altman plots suggested no fixed errors between the proposed method and the optical motion capture system. These results suggest that the proposed method could be utilized for measuring foot position during assistive motion for sit-to-stand.

scholarly journals An open-source and wearable system for measuring 3D human motion in real-time

2021 ◽  
Author(s):  
Patrick Slade ◽  
Ayman Habib ◽  
Jennifer L. Hicks ◽  
Scott L. Delp
Keyword(s):  
Open Source ◽  
Real Time ◽  
Motion Capture ◽  
Human Motion ◽  
Sensor Systems ◽  
Wearable Sensor ◽  
Joint Angles ◽  
Wearable System ◽  
Optical Motion ◽  
Optical Motion Capture

AbstractAnalyzing human motion is essential for diagnosing movement disorders and guiding rehabilitation interventions for conditions such as osteoarthritis, stroke, and Parkinson’s disease. Optical motion capture systems are the current standard for estimating kinematics but require expensive equipment located in a predefined space. While wearable sensor systems can estimate kinematics in any environment, existing systems are generally less accurate than optical motion capture. Further, many wearable sensor systems require a computer in close proximity and rely on proprietary software, making it difficult for researchers to reproduce experimental findings. Here, we present OpenSenseRT, an open-source and wearable system that estimates upper and lower extremity kinematics in real time by using inertial measurement units and a portable microcontroller. We compared the OpenSenseRT system to optical motion capture and found an average RMSE of 4.4 degrees across 5 lower-limb joint angles during three minutes of walking (n = 5) and an average RMSE of 5.6 degrees across 8 upper extremity joint angles during a Fugl-Meyer task (n = 5). The open-source software and hardware are scalable, tracking between 1 and 14 body segments, with one sensor per segment. Kinematics are estimated in real-time using a musculoskeletal model and inverse kinematics solver. The computation frequency, depends on the number of tracked segments, but is sufficient for real-time measurement for many tasks of interest; for example, the system can track up to 7 segments at 30 Hz in real-time. The system uses off-the-shelf parts costing approximately $100 USD plus $20 for each tracked segment. The OpenSenseRT system is accurate, low-cost, and simple to replicate, enabling movement analysis in labs, clinics, homes, and free-living settings.

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