scholarly journals Development and Research of a Multi-Medium Motion Capture System for Underwater Intelligent Agents

2020 ◽  
Vol 10 (18) ◽  
pp. 6237
Author(s):  
Zhongpan Zhu ◽  
Xin Li ◽  
Zhipeng Wang ◽  
Luxi He ◽  
Bin He ◽  
...  
Keyword(s):  
Motion Capture ◽  
Intelligent Agents ◽  
Clustering Algorithm ◽  
Visual Detection ◽  
Three Dimensional ◽  
Motion Capture System ◽  
Refraction Effect ◽  
Robot Fish ◽  
2D Data ◽  
Reconstruction Model

A multi-medium motion capture system based on markers’ visual detection is developed and experimentally demonstrated for monitoring underwater intelligent agents such as fish biology and bionic robot-fish. Considering the refraction effect between air and water, a three-dimensional (3D) reconstruction model is established, which can be utilized to reconstruct the 3D coordinate of markers underwater from 2D data. Furthermore, the process of markers matching is undertaken through the multi-lens fusion perception prediction combined K-Means clustering algorithm. Subsequently, in order to track the marker of being occluded, according to the kinematics information of fish, an improved Kalman filtering algorithm is proposed. Finally, the feasibility and effectiveness of proposed system are verified through experimental results. The main models and methods in this paper can provide a reference and inspiration for measurement of underwater intelligent agents.

A Low-Dimensional Dissimilarity Analysis of Unilateral and Bilateral Stroke-Impacted Hand Trajectories

2016 ◽  
Vol 138 (11) ◽  
Author(s):  
Jay Ryan U. Roldan ◽  
Dejan Milutinović ◽  
Zhi Li ◽  
Jacob Rosen
Keyword(s):  
Multidimensional Scaling ◽  
Healthy Subject ◽  
Motion Capture ◽  
Early Phase ◽  
Three Dimensional ◽  
High Rate ◽  
Motion Capture System ◽  
Trajectory Data ◽  
The Difference ◽  
Low Dimensional

In this paper, we propose a quantitative approach based on identifying hand trajectory dissimilarities through the use of a multidimensional scaling (MDS) analysis. A high-rate motion capture system is used to gather three-dimensional (3D) trajectory data of healthy and stroke-impacted hemiparetic subjects. The mutual dissimilarity between any two trajectories is measured by the area between them. This area is used as a dissimilarity variable to create an MDS map. The map reveals a structure for measuring the difference and variability of individual trajectories and their groups. The results suggest that the recovery of hemiparetic subjects can be quantified by comparing the difference and variability of their individual MDS map points to the points from the cluster of healthy subject trajectories. Within the MDS map, we can identify fully recovered patients, those who are only functionally recovered, and those who are either in an early phase of, or are nonresponsive to the therapy.

A Mobile Motion Capture System Based on Inertial Sensors and Smart Shoes

2013 ◽  
Vol 136 (1) ◽  
Author(s):  
Pyeong-Gook Jung ◽  
Sehoon Oh ◽  
Gukchan Lim ◽  
Kyoungchul Kong
Keyword(s):  
Motion Capture ◽  
Inertial Sensors ◽  
Kinematic Model ◽  
Three Dimensional ◽  
Health Condition ◽  
Body Motion ◽  
Whole Body ◽  
Motion Capture System ◽  
Outdoor Sports ◽  
Motion Capture Systems

Motion capture systems play an important role in health-care and sport-training systems. In particular, there exists a great demand on a mobile motion capture system that enables people to monitor their health condition and to practice sport postures anywhere at any time. The motion capture systems with infrared or vision cameras, however, require a special setting, which hinders their application to a mobile system. In this paper, a mobile three-dimensional motion capture system is developed based on inertial sensors and smart shoes. Sensor signals are measured and processed by a mobile computer; thus, the proposed system enables the analysis and diagnosis of postures during outdoor sports, as well as indoor activities. The measured signals are transformed into quaternion to avoid the Gimbal lock effect. In order to improve the precision of the proposed motion capture system in an open and outdoor space, a frequency-adaptive sensor fusion method and a kinematic model are utilized to construct the whole body motion in real-time. The reference point is continuously updated by smart shoes that measure the ground reaction forces.

Estimation of baseball bat trajectory during a practice swing using a Kalman filter for velocity compensation

2019 ◽  
pp. 175433711987143
Author(s):  
Shohei Shibata ◽  
Kiyoshi Hirose ◽  
Takeshi Naruo ◽  
Yuichi Shimizu
Keyword(s):  
Kalman Filter ◽  
Root Mean Square ◽  
Sensor Fusion ◽  
Motion Capture ◽  
Time Integration ◽  
Three Dimensional ◽  
Forward Direction ◽  
Mean Square ◽  
Motion Capture System ◽  
Motion Characteristics

This study aimed to (a) develop an algorithm that could estimate a baseball bat trajectory from the beginning of the swing to the follow-through phase during a practice swing without a ball and (b) evaluate the accuracy of the proposed method using a three-dimensional motion capture system. The sensor fusion using the adaptive Kalman filter for compensating velocity decreased the error of acceleration integration during the follow-through phase. Further, the three-dimensional bat trajectory in a global coordinate was estimated by combining the sensor fusion and compensation by motion characteristics. The three-dimensional bat trajectory from the swing beginning to the follow-through phase estimated by the proposed method was compared with the three-dimensional bat trajectory obtained by the three-dimensional motion capture system. The proposed method achieved a root mean square of the error of 7.72 km/h for velocity, which was less than the root mean square of the error (8.91 km/h) obtained by simple time integration of forward direction. These results indicate that the error by acceleration integration during the follow-through phase is compensated. The proposed method is, thus, deemed effective and can be used to evaluate baseball swing, including the follow-through phase, with high accuracy.

Design of Multi-User Aerobics Wireless Human Motion Capture System Based on MEMS

2013 ◽  
Vol 650 ◽  
pp. 518-522
Author(s):  
Juan Xiao
Keyword(s):  
Real Time ◽  
Motion Capture ◽  
Large Scale ◽  
Three Dimensional ◽  
Human Motion ◽  
Motion Capture System ◽  
Human Motion Capture ◽  
Large Scale Data ◽  
Core Technology ◽  
Real Time Transmission

Main characteristics of recent human motion capture systems are analyzed in the paper firstly. Based on that, a new multi-user aerobics wireless human motion capture system based on MEMS is proposed. Design of its framework and core technology solutions including large-scale data obtain, multi-hop wireless sensor and high-frequency real-time transmission are put forward. Finally, three-dimensional real-time reconstructions of the multi-user aerobics wireless motion capture system are showed in the paper.

Apparel ease distribution analysis using three-dimensional motion capture

2019 ◽  
Vol 89 (19-20) ◽  
pp. 4323-4335 ◽  
Author(s):  
Zheng Liu ◽  
Qin He ◽  
Fengyuan Zou ◽  
Yuyan Ding ◽  
Bugao Xu
Keyword(s):  
Motion Capture ◽  
Walking Speed ◽  
Three Dimensional ◽  
Distribution Analysis ◽  
Motion Capture System ◽  
Dynamic Tests ◽  
Body Type ◽  
Changing Patterns ◽  
Left And Right ◽  
Ease Allowance

When an ease allowance at a body landmark is given, the ease distribution along the circumference at this landmark can still change with the wearing circumstance. This paper investigates both static and dynamic ease distributions of clothes at bust and waist lines by using a three-dimensional motion capture system (3DMCS). Female participants with the same body type were recruited to conduct experiments to examine how ease distributions change with body motions. Specific markers provided with the 3DMCS were adhered to the surfaces of a participant and her clothes along the bust and waist lines, and the coordinates of the markers were tracked by the 3DMCS while the participant walked on a treadmill at different speeds. It was found that the static ease distributions showed different patterns at different body landmark lines. At the bust, the ease tended to concentrate more in the left and right regions, while the ease at the waist appeared to be gathered more in the front and back regions. In the dynamic tests, ease variations at different clothes markers on the waistline exhibited very different changing patterns. The ease variations of the markers in the same region (e.g., left and front) were positively correlated ( r = 0.863), while those in regions symmetrical to the y-axis (left–right) were negatively correlated ( r = –0.738) and those in regions symmetrical to the x-axis (front–back) were weakly correlated ( r = 0.541). Both the frequency and the magnitude of ease variations seemed to be incremental to the walking speed, although the concentration areas of ease remained unchanged.

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