scholarly journals Use of computer innovative technologies in improving the dartsmen training

2020 ◽  
Vol 26 ◽  
pp. 00061
Author(s):  
Elina Makarova ◽  
Vladislav Dubatovkin ◽  
Nataliya Berezinskaya ◽  
Lyudmila Barkhatova ◽  
Elena Oleynik
Keyword(s):  
Motion Capture ◽  
Body Parts ◽  
Visual Material ◽  
Video Cameras ◽  
Dart Throwing ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Effective Use ◽  
Near Future ◽  
Motion Capture Systems

The research is focused on studying the possibility of effective use of the dart grip system, the work of the athlete’s hand, to prepare the dartsman for competitions using the MOSAR complex. The experiment uses optical motion capture systems, a set of video cameras, led parameter sensors, and devices that allow to record the movement of body parts and a dart. This method of training and controlling dart throwing can serve as educational and visual material for training future athletes. The use of such motion capture systems in the near future may become one of the main aspects of training, both beginners and professionals, in many sports.

DEVELOPMENT OF MOTION CAPTURE SYSTEM USING DUAL VIDEO CAMERAS FOR THE GAIT DESIGN OF A BIPED ROBOT

2011 ◽  
Vol 08 (02) ◽  
pp. 275-299 ◽  
Author(s):  
JUNG-YUP KIM ◽  
YOUNG-SEOG KIM
Keyword(s):  
Motion Capture ◽  
Human Walking ◽  
Human Gait ◽  
Motion Capture System ◽  
System Calibration ◽  
Walking Gait ◽  
Video Cameras ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Motion Capture Systems

This paper, describes the development of a motion capture system with novel features for biped robots. In general, motion capture is effectively utilized in the field of computer animation. In the field of humanoid robotics, the number of studies attempting to design human-like gaits by using expensive optical motion capture systems is increasing. The optical motion capture systems used in these studies have involved a large number of cameras because such systems use small-sized ball markers; hence the position accuracy of the markers and the system calibration are very significant. However, since the human walking gait is a simple periodic motion rather than a complex motion, we have developed a specialized motion capture system for this study using dual video cameras and large band-type markers without high-level system calibration in order to capture the human walking gait. In addition to its lower complexity, the proposed capture method requires only a low-cost system and has high space efficiency. An image processing algorithm is also proposed for deriving the human gait data. Finally, we verify the reliability and accuracy of our system by comparing a zero moment point (ZMP) trajectory calculated by the motion captured data with a ZMP trajectory measured by foot force sensors.

Embodiment in Electronic Dance Music: Effects of musical content and structure on body movement

2018 ◽  
Vol 24 (2) ◽  
pp. 186-205 ◽  
Author(s):  
Birgitta Burger ◽  
Petri Toiviainen
Keyword(s):  
Motion Capture ◽  
Body Movement ◽  
Personality Characteristics ◽  
Body Parts ◽  
Dance Music ◽  
Electronic Dance Music ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Hands And Feet ◽  
Music Effects

Electronic dance music (EDM) is music produced with the foremost aim to make people move. While research has revealed relationships between movement features and, for example, musical, emotional, or personality characteristics, systematic investigations of genre differences and specifically of EDM are rather rare. This article aims at offering insights into the embodiment of EDM from three different angles: first from a genre-comparison perspective, then by comparing different EDM stimuli with each other, and finally by investigating embodiments in one specific EDM stimulus. Sixty participants moved freely to 16 stimuli of four different genres (EDM, Latin, Funk, Jazz – four stimuli/genre) while being recorded with an optical motion capture system. Subsequently, a set of movement features was extracted from the motion capture data. Results indicate that participants moved with significantly higher acceleration of torso, head, hands, and feet and more overall movement to the EDM stimuli than to the other genres. Between EDM stimuli, several significant correlations were found, suggesting an increase in acceleration of different body parts with clearer and more percussive rhythmic structures and brighter sounds. Within one EDM stimulus, participants’ movements differed in several movement features distinguishing the break from surrounding sections, showing less acceleration, as well as less overall movement and rotational speed during the break. These analyses propose different ways of studying EDM and indicate distinctive characteristics of EDM embodiment.

scholarly journals Use of the Azure Kinect to measure foot clearance during obstacle crossing

2021 ◽  
Author(s):  
Kohei Yoshimoto ◽  
Masahiro Shinya
Keyword(s):  
Motion Capture ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Random Errors ◽  
Obstacle Crossing ◽  
Risk Of Falls ◽  
Optical Motion ◽  
Foot Clearance ◽  
Optical Motion Capture ◽  
Motion Capture Systems

Obstacle crossing is a typical adaptive locomotion known to be related to the risk of falls. Previous conventional studies have used elaborate and costly optical motion capture systems, which not only represent a considerable expense but also require participants to visit a laboratory. To overcome these shortcomings, we aimed to develop a practical and inexpensive solution for measuring obstacle-crossing behavior by using the Microsoft Azure Kinect, one of the most promising markerless motion capture systems. We validated the Azure Kinect as a tool to measure foot clearance and compared its performance to that of an optical motion capture system (Qualisys). We also determined the effect of the Kinect sensor placement on measurement performance. Sixteen healthy young men crossed obstacles of different heights (50, 150, and 250 mm). Kinect sensors were placed in front of and beside the obstacle as well as diagonally between those positions. As indices of measurement quality, we counted the number of measurement failures and calculated the systematic and random errors between the foot clearance measured by the Kinect and Qualisys. We also calculated the Pearson correlation coefficients between the Kinect and Qualisys measurements. The number of measurement failures and the systematic and random error were minimized when the Kinect was placed diagonally in front of the obstacle on the same side as the trail limb. The high correlation coefficient (r > 0.890) observed between the Kinect and Qualisys measurements suggests that the Azure Kinect has excellent potential for measuring foot clearance during obstacle-crossing tasks.

Non-rigid alignment pipeline applied to human gait signals acquired with optical motion capture systems and inertial sensors

2020 ◽  
Vol 98 ◽  
pp. 109429 ◽  
Author(s):  
Rubén Soussé ◽  
Jorge Verdú ◽  
Ricardo Jauregui ◽  
Ventura Ferrer-Roca ◽  
Simone Balocco
Keyword(s):  
Motion Capture ◽  
Inertial Sensors ◽  
Human Gait ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Motion Capture Systems

scholarly journals Evaluation of 3D markerless motion capture accuracy using OpenPose with multiple video cameras

2019 ◽  
Author(s):  
Nobuyasu Nakano ◽  
Tetsuro Sakura ◽  
Kazuhiro Ueda ◽  
Leon Omura ◽  
Arata Kimura ◽  
...  
Keyword(s):  
Motion Capture ◽  
Human Movement ◽  
Absolute Error ◽  
Motor Tasks ◽  
3D Pose Estimation ◽  
Video Cameras ◽  
Markerless Motion Capture ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Capture Technique

AbstractThere is a need within human movement sciences for a markerless motion capture system, which is easy to use and suffciently accurate to evaluate motor performance. This study aims to develop a 3D markerless motion capture technique, using OpenPose with multiple synchronized video cameras, and examine its accuracy in comparison with optical marker-based motion capture. Participants performed three motor tasks (walking, countermovement jumping, and ball throwing), with these movements measured using both marker-based optical motion capture and OpenPose-based markerless motion capture. The differences in corresponding joint positions, estimated from the two different methods throughout the analysis, were presented as a mean absolute error (MAE). The results demonstrated that, qualitatively, 3D pose estimation using markerless motion capture could correctly reproduce the movements of participants. Quantitatively, of all the mean absolute errors calculated, approximately 47% were less than 20 mm and 80% were less than 30 mm. However, 10% were greater than 40 mm. The primary reason for mean absolute errors exceeding 40mm was that OpenPose failed to track the participant’s pose in 2D images owing to failures, such as recognition of an object as a human body segment, or replacing one segment with another depending on the image of each frame. In conclusion, this study demonstrates that, if an algorithm that corrects all apparently wrong tracking can be incorporated into the system, OpenPose-based markerless motion capture can be used for human movement science with an accuracy of 30mm or less.

scholarly journals Concurrent assessment of gait kinematics using marker-based and markerless motion capture

2020 ◽  
Author(s):  
Robert Kanko ◽  
Elise Laende ◽  
Elysia Davis ◽  
W. Scott Selbie ◽  
Kevin J. Deluzio
Keyword(s):  
Motion Capture ◽  
Lower Limb ◽  
Video Data ◽  
Motion Capture System ◽  
Kinematic Data ◽  
Markerless Motion Capture ◽  
Common Marker ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Motion Capture Systems

AbstractKinematic analysis is a useful and widespread tool used in research and clinical biomechanics for the estimation of human pose and the quantification of human movement. Common marker-based optical motion capture systems are expensive, time intensive, and require highly trained operators to obtain kinematic data. Markerless motion capture systems offer an alternative method for the measurement of kinematic data with several practical benefits. This work compared the kinematics of human gait measured using a deep learning algorithm-based markerless motion capture system to those of a common marker-based motion capture system. Thirty healthy adult participants walked on a treadmill while data were simultaneously recorded using eight video cameras (markerless) and seven infrared optical motion capture cameras (marker-based). Video data were processed using markerless motion capture software, marker-based data were processed using marker-based capture software, and both sets of data were compared. The average root mean square distance (RMSD) between corresponding joints was less than 3 cm for all joints except the hip, which was 4.1 cm. Lower limb segment angles indicated pose estimates from both systems were very similar, with RMSD of less than 6° for all segment angles except those that represent rotations about the long axis of the segment. Lower limb joint angles captured similar patterns for flexion/extension at all joints, ab/adduction at the knee and hip, and toe-in/toe-out at the ankle. These findings demonstrate markerless motion capture can measure similar 3D kinematics to those from marker-based systems.

scholarly journals Performance of Optical Structural Vibration Monitoring Systems in Experimental Modal Analysis

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1239
Author(s):  
Maksat Kalybek ◽  
Mateusz Bocian ◽  
Nikolaos Nikitas
Keyword(s):  
Modal Analysis ◽  
Motion Capture ◽  
Experimental Modal Analysis ◽  
Vibration Monitoring ◽  
Structural Vibration ◽  
Monitoring Systems ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Motion Capture Systems ◽  
Optical Vibration

Image-based optical vibration measurement is an attractive alternative to the conventional measurement of structural dynamics predominantly relying on accelerometry. Although various optical vibration monitoring systems are now readily available, their performance is currently not well defined, especially in the context of experimental modal analysis. To this end, this study provides some of the first evidence of the capability of optical vibration monitoring systems in modal identification using input–output measurements. A comparative study is conducted on a scaled model of a 3D building frame set in a laboratory environment. The dynamic response of the model to an impulse excitation from an instrumented hammer, and an initial displacement, is measured by means of five optical motion capture systems. These include commercial and open-source systems based on laser Doppler velocimetry, fiducial markers and marker-less pattern recognition. The performance of these systems is analysed against the data obtained with a set of high-precision accelerometers. It is shown that the modal parameters identified from each system are not always equivalent, and that each system has limitations inherent to its design. Informed by these findings, a guidance for the deployment of the considered optical motion capture systems is given, aiding in their choice and implementation for structural vibration monitoring.

Tracking of Markers for 2D and 3D Gait Analysis Using Home Video Cameras

2013 ◽  
Vol 4 (3) ◽  
pp. 36-52 ◽  
Author(s):  
Sandro Mihradi ◽  
Ferryanto ◽  
Tatacipta Dirgantara ◽  
Andi I. Mahyuddin
Keyword(s):  
Gait Analysis ◽  
Motion Capture ◽  
Motion Capture System ◽  
Distance Method ◽  
Home Video ◽  
Video Cameras ◽  
Optical Motion ◽  
Spatio Temporal ◽  
Optical Motion Capture ◽  
2D And 3D

This work presents the development of an affordable optical motion-capture system which uses home video cameras for 2D and 3D gait analysis. The 2D gait analyzer system consists of one camcorder and one PC while the 3D gait analyzer system uses two camcorders, a flash and two PCs. Both systems make use of 25 fps camcorder, LED markers and technical computing software to track motions of markers attached to human body during walking. In the experiment for 3D gait analyzer system, the two cameras are synchronized by using flash. The recorded videos for both systems are extracted into frames and then converted into binary images, and bridge morphological operation is applied for unconnected pixel to facilitate marker detection process. Least distance method is then employed to track the markers motions, and 3D Direct Linear Transformation is used to reconstruct 3D markers positions. The correlation between length in pixel and in the real world resulted from calibration process is used to reconstruct 2D markers positions. To evaluate the reliability of the 2D and 3D optical motion-capture system developed in the present work, spatio-temporal and kinematics parameters calculated from the obtained markers positions are qualitatively compared with the ones from literature, and the results show good compatibility.

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