Automatic bone parameter estimation for skeleton tracking in 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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Use of computer innovative technologies in improving the dartsmen training

BIO Web of Conferences ◽

10.1051/bioconf/20202600061 ◽

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.

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Human Motion Capture Driven by Orientation Measurements

Presence Teleoperators & Virtual Environments ◽

10.1162/105474699566161 ◽

1999 ◽

Vol 8 (2) ◽

pp. 187-203 ◽

Cited By ~ 24

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.

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