Enhancing Motion Capture Performance by Means of an Internal Anthropometric Skeleton Model

2008 ◽  
Author(s):  
Matthias Weber ◽  
Thomas Alexander ◽  
Heni Ben Amor
Keyword(s):  
Motion Capture ◽  
Skeleton Model

scholarly journals A Markerless 3D Computerized Motion Capture System Incorporating a Skeleton Model for Monkeys

PLoS ONE ◽  
2016 ◽  
Vol 11 (11) ◽  
pp. e0166154 ◽  
Author(s):  
Tomoya Nakamura ◽  
Jumpei Matsumoto ◽  
Hiroshi Nishimaru ◽  
Rafael Vieira Bretas ◽  
Yusaku Takamura ◽  
...  
Keyword(s):  
Motion Capture ◽  
Motion Capture System ◽  
Skeleton Model

Research on Wearable Human Motion Capture and Virtual Control

2014 ◽  
Vol 686 ◽  
pp. 121-125
Author(s):  
Fei Jiang ◽  
Ying Jie Yu ◽  
Da Wei Yan
Keyword(s):  
Real Time ◽  
Motion Capture ◽  
Inertial Sensor ◽  
Calibration Method ◽  
Human Motion ◽  
Skeleton Model ◽  
Body Attitude ◽  
Human Limb ◽  
Coordinate Conversion ◽  
Skeletal Model

This paper designed the posture initialization calibration method by the inertial sensor in human limb movement with any attitude toward. By initializing the target specific actions can be implemented to identify timing corresponding sensors and joint, and calculate the coordinate transformation relation of human skeletal coordinates corresponding to each inertial sensor's coordinate system and the 3D human skeleton model. Then through the coordinate conversion of inertial sensor attitude coordinates and depth first traversal calculation on human skeletal tree, real-time update of human motion body attitude data, driven simulation of human skeletal model by human motion, realize the real-time tracking of motion capture.

scholarly journals Real-Time Human Motion Capture Driven by a Wireless Sensor Network

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Peng-zhan Chen ◽  
Jie Li ◽  
Man Luo ◽  
Nian-hua Zhu
Keyword(s):  
Real Time ◽  
Sensor Network ◽  
Motion Capture ◽  
Human Motion ◽  
Human Model ◽  
Human Skeleton ◽  
Inertial Sensing ◽  
Skeleton Model ◽  
Human Motion Capture ◽  
Motion Capture Systems

The motion of a real object model is reconstructed through measurements of the position, direction, and angle of moving objects in 3D space in a process called “motion capture.” With the development of inertial sensing technology, motion capture systems that are based on inertial sensing have become a research hot spot. However, the solution of motion attitude remains a challenge that restricts the rapid development of motion capture systems. In this study, a human motion capture system based on inertial sensors is developed, and the real-time movement of a human model controlled by real people’s movement is achieved. According to the features of the system of human motion capture and reappearance, a hierarchical modeling approach based on a 3D human body model is proposed. The method collects articular movement data on the basis of rigid body dynamics through a miniature sensor network, controls the human skeleton model, and reproduces human posture according to the features of human articular movement. Finally, the feasibility of the system is validated by testing of system properties via capture of continuous dynamic movement. Experiment results show that the scheme utilizes a real-time sensor network-driven human skeleton model to achieve the accurate reproduction of human motion state. The system also has good application value.

A Virtual Human's Driving Method Based on Motion Capture Data

2013 ◽  
Vol 711 ◽  
pp. 500-505 ◽  
Author(s):  
Song Shan Wang ◽  
Yan Qing Qi
Keyword(s):  
Motion Capture ◽  
Euler Angle ◽  
Human Motion ◽  
Virtual Human ◽  
Motion Capture Data ◽  
Joint Angles ◽  
Skeleton Model ◽  
Angle Rotation ◽  
Set Up

This article gives a method about driving a virtual human by motion capture data in software Jack. Firstly simplify Jack's skeleton model according to the skeleton of capturing data BVH. Secondly set up an Euler angle rotation equation to mapping joint angles between BVH and Jack. Finally, program the method and give an example to show that it is available to improve Jacks human motion simulating by the human capturing data.

scholarly journals Wide Area Motion Tracking Using Consumer Hardware

2013 ◽  
Vol 12 (1) ◽  
pp. 57-65
Author(s):  
Christian Schönauer ◽  
Hannes Kaufmann
Keyword(s):  
Motion Capture ◽  
Local Area Network ◽  
Tracking System ◽  
Local Area ◽  
Wide Area ◽  
Area Network ◽  
Skeleton Model ◽  
Pose Tracking ◽  
Human Movements ◽  
Human Pose

In this paper we present a wide area tracking system based on consumer hardware and available motion capture modules and middleware. We are using multiple depth cameras for human pose tracking in order to increase the captured space. Commercially available cameras can capture human movements in a non-intrusive way, while associated software-modules produce pose information of a simplified skeleton model. We calibrate the cameras relatively to each other to seamlessly combine their tracking data. Our design allows an arbitrary number of sensors to be integrated and used in parallel over a local area network. This enables us to capture human movements in a large arbitrarily shaped area. In addition we can improve motion capture data in regions, where the field of view of multiple cameras overlaps, by mutually completing partly occluded poses. In various examples we demonstrate, how human pose data is being merged in order to cover a wide area and how this data can easily be used for character animation in a virtual environment.

scholarly journals Improved 3D Human Motion Capture Using Kinect Skeleton and Depth Sensor

2021 ◽  
Vol 33 (6) ◽  
pp. 1408-1422
Author(s):  
Alireza Bilesan ◽  
Shunsuke Komizunai ◽  
Teppei Tsujita ◽  
Atsushi Konno ◽  
◽  
...  
Keyword(s):  
Motion Capture ◽  
Correlation Coefficients ◽  
Ground Truth ◽  
Cost Effective ◽  
Human Motion ◽  
Human Gait ◽  
Joint Angles ◽  
Kinematic Parameters ◽  
Depth Sensor ◽  
Skeleton Model

Kinect has been utilized as a cost-effective, easy-to-use motion capture sensor using the Kinect skeleton algorithm. However, a limited number of landmarks and inaccuracies in tracking the landmarks’ positions restrict Kinect’s capability. In order to increase the accuracy of motion capturing using Kinect, joint use of the Kinect skeleton algorithm and Kinect-based marker tracking was applied to track the 3D coordinates of multiple landmarks on human. The motion’s kinematic parameters were calculated using the landmarks’ positions by applying the joint constraints and inverse kinematics techniques. The accuracy of the proposed method and OptiTrack (NaturalPoint, Inc., USA) was evaluated in capturing the joint angles of a humanoid (as ground truth) in a walking test. In order to evaluate the accuracy of the proposed method in capturing the kinematic parameters of a human, lower body joint angles of five healthy subjects were extracted using a Kinect, and the results were compared to Perception Neuron (Noitom Ltd., China) and OptiTrack data during ten gait trials. The absolute agreement and consistency between each optical system and the robot data in the robot test and between each motion capture system and OptiTrack data in the human gait test were determined using intraclass correlations coefficients (ICC3). The reproducibility between systems was evaluated using Lin’s concordance correlation coefficient (CCC). The correlation coefficients with 95% confidence intervals (95%CI) were interpreted substantial for both OptiTrack and proposed method (ICC > 0.75 and CCC > 0.95) in humanoid test. The results of the human gait experiments demonstrated the advantage of the proposed method (ICC > 0.75 and RMSE = 1.1460°) over the Kinect skeleton model (ICC < 0.4 and RMSE = 6.5843°).

scholarly journals Design and implementation of Peking Opera action scoring system based on human skeleton information

2018 ◽  
Vol 232 ◽  
pp. 01026 ◽  
Author(s):  
Hang Zhao ◽  
Youdong Ding ◽  
Bing Yu ◽  
Chenfeng Jiang ◽  
Wanying Zhang
Keyword(s):  
Motion Capture ◽  
Scoring System ◽  
Body Part ◽  
Human Action ◽  
Human Skeleton ◽  
Skeleton Model ◽  
Software Interface ◽  
Peking Opera ◽  
Optical Motion ◽  
Optical Motion Capture

At present, most of the preservation records of Peking Opera remain in the ways of video and text, and the digitalization degree is far lower than the development level of science and technology. The immaterial cultural heritage cannot be fully displayed and Peking Opera’s value is weakened. Therefore, adopting advanced motion capture technology is of great significance to the protection and inheritance of Peking Opera. We use optical motion capture equipment to record the movement information of Peking Opera actors, then keep the human skeleton information in a specific file format. After that, the hierarchical human action skeleton model was analysed, and the final score was obtained by comparing the change sequence of information of reference action and training action skeleton with the improved DTW algorithm. We have realized the graphical interface of the system, and the trainer can easily select the action segments to train or select a specific body part for specific action training. This paper introduces the overall design framework of our Peking Opera action scoring system, including the collection of action information, the implementation of scoring algorithm and the design of software interface.

Correlational Methods for Analysis of Dance Movements

2011 ◽  
Vol 29 (supplement) ◽  
pp. 283-304 ◽  
Author(s):  
Timothy R. Brick ◽  
Steven M. Boker
Keyword(s):  
Motion Capture ◽  
Mirror Symmetry ◽  
Cross Correlation ◽  
The Other ◽  
Free Form ◽  
Motion Capture Data ◽  
Complex Interactions ◽  
Dance Movements ◽  
Time Lagged ◽  
Insight Into

Among the qualities that distinguish dance from other types of human behavior and interaction are the creation and breaking of synchrony and symmetry. The combination of symmetry and synchrony can provide complex interactions. For example, two dancers might make very different movements, slowing each time the other sped up: a mirror symmetry of velocity. Examining patterns of synchrony and symmetry can provide insight into both the artistic nature of the dance, and the nature of the perceptions and responses of the dancers. However, such complex symmetries are often difficult to quantify. This paper presents three methods – Generalized Local Linear Approximation, Time-lagged Autocorrelation, and Windowed Cross-correlation – for the exploration of symmetry and synchrony in motion-capture data as is it applied to dance and illustrate these with examples from a study of free-form dance. Combined, these techniques provide powerful tools for the examination of the structure of symmetry and synchrony in dance.

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