A physics-based approach to motion capture data processing for virtual plant modeling and simulation

2018 ◽  
Vol 09 (03) ◽  
pp. 1840005
Author(s):  
Boxiang Xiao ◽  
Sheng Wu ◽  
Xinyu Guo
Keyword(s):  
Data Processing ◽  
Motion Capture ◽  
Dynamic Mechanical Properties ◽  
Primary Data ◽  
Model Parameters ◽  
Motion Capture Data ◽  
Motion Data ◽  
Virtual Plant ◽  
Mechanics Model ◽  
Tool Motion

Dynamic virtual plant simulation is an attractive research issue in both botany and computer graphics. Data-driven method is an efficient way for motion analysis and animation synthesis. As a widely used tool, motion capture has been used in plant motion data acquisition and analysis. The most prominent and important problem in motion capture for plants is primary data processing such as missing markers reconstruction. This paper presents a novel physics-based approach to motion capture data processing of plants. Firstly, a physics-based mechanics model is found by Lagrangian mechanics for a motion captured plant organ such as a leaf, and then its dynamic mechanical properties are analyzed and relevant model parameters are evaluated. Further, by using the physical model with evaluated parameters, we can calculate the next positions of a maker to reconstruct the missing makers in motion capture sequence. We take an example of a maize leaf and pachira leaf to examine the proposed approach, and the results show that the physics-based method is feasible and effective for plant motion data processing.

CONTROLLING A MOTORIZED MARIONETTE WITH HUMAN MOTION CAPTURE DATA

2004 ◽  
Vol 01 (04) ◽  
pp. 651-669 ◽  
Author(s):  
KATSU YAMANE ◽  
JESSICA K. HODGINS ◽  
H. BENJAMIN BROWN
Keyword(s):  
Motion Capture ◽  
Degrees Of Freedom ◽  
Dynamic Properties ◽  
Human Motion ◽  
Data Sets ◽  
Motion Capture Data ◽  
Sensors And Actuators ◽  
Human Motion Capture ◽  
Motion Data ◽  
Human Actors

In this paper, we present a method for controlling a motorized, string-driven marionette using motion capture data from human actors and from a traditional marionette operated by a professional puppeteer. We are interested in using motion capture data of a human actor to control the motorized marionette as a way of easily creating new performances. We use data from the hand-operated marionette both as a way of assessing the performance of the motorized marionette and to explore whether this technology could be used to preserve marionette performances. The human motion data must be extensively adapted for the marionette because its kinematic and dynamic properties differ from those of the human actor in degrees of freedom, limb length, workspace, mass distribution, sensors, and actuators. The motion from the hand-operated marionette requires less adaptation because the controls and dynamics are a closer match. Both data sets are adapted using an inverse kinematics algorithm that takes into account marker positions, joint motion ranges, string constraints, and potential energy. We also apply a feedforward controller to prevent extraneous swings of the hands. Experimental results show that our approach enables the marionette to perform motions that are qualitatively similar to the original human motion capture data.

Study on Feature Extraction Methods Based on Motion Capture Data

2014 ◽  
Vol 926-930 ◽  
pp. 2114-2117
Author(s):  
Yong Dan Nie ◽  
Yan Zhang ◽  
Xian Mei Liu
Keyword(s):  
Feature Extraction ◽  
Motion Capture ◽  
Extraction Method ◽  
Data Retrieval ◽  
Extraction Methods ◽  
Motion Capture Data ◽  
Motion Feature ◽  
Feature Extraction Method ◽  
Motion Data ◽  
Analysis Of Motion

By the analysis of motion Geometric features and Continuing feature that the motion capture data of the BVH format showed,Motion feature extraction method was proposed in this paper to preserve the motion original features in the maximum extent and marked motion data,improved the speed of motion data retrieval,and also provided a new method for rendering of motion characters in the virtual environment.

scholarly journals A retrieval method for human Mocap data based on biomimetic pattern recognition

2010 ◽  
Vol 7 (1) ◽  
pp. 99-109
Author(s):  
Xiaopeng Wei ◽  
Boxiang Xiao ◽  
Qiang Zhang
Keyword(s):  
Pattern Recognition ◽  
Motion Capture ◽  
Distribution Range ◽  
Experimental Results ◽  
Free Motion ◽  
Retrieval Algorithm ◽  
Motion Capture Data ◽  
Retrieval Method ◽  
Motion Data

A retrieval method for human Mocap (Motion Capture) data based on biomimetic pattern recognition is presented in this paper. BVH rotation channels are extracted as features of motion for both the retrieval instance and the motion data. Several hyper sausage neurons are constructed according to the retrieval instance, and the trained domain covered by these hyper sausage neurons can be considered as the distribution range of a same kind of motions. By use of CMU free motion database, the retrieval algorithm has been implemented and examined, and the experimental results are illustrated. At the same time, the main contributions and limitations are discussed.

scholarly journals A METHOD FOR VISUALIZATION OF 3D MOTION DATA USING A MOBILE DEVICE

2017 ◽  
Vol 7 (3) ◽  
pp. 37-42 ◽  
Author(s):  
Michał Oseńko ◽  
Jakub Smołka ◽  
Maria Skublewska-Paszkowska ◽  
Edyta Łukasik
Keyword(s):  
Virtual Reality ◽  
Motion Capture ◽  
Mobile Device ◽  
Motion Capture Data ◽  
3D Motion ◽  
Motion Data ◽  
Innovative Method ◽  
File Formats

3D motion visualization is a topic closely connected with motion capture. Motion capture data come in many file formats, one of which is C3D. The following paper presents an innovative method of motion visualization in virtual reality using Google Cardboard. Motion data are read from C3D files. The paper presents introduction to the technology used, analysis of existing solutions, presentation of the proposed method, its implementation and results.

A Survey on Motion Capture Data Retrieval

2014 ◽  
Vol 556-562 ◽  
pp. 2944-2947 ◽  
Author(s):  
Na Lv ◽  
Yan Huang ◽  
Zhi Quan Feng ◽  
Jing Liang Peng
Keyword(s):  
Motion Capture ◽  
Computer Animation ◽  
Rapid Development ◽  
Data Retrieval ◽  
Motion Capture Data ◽  
Motion Data ◽  
Existing Problems ◽  
Large Motion

With the rapid development of motion capture technology, large motion capture databases are established. How to effectively retrieve the motions from huge amounts of motion data has become a hot topic in computer animation. In this paper, we give a survey on current motion capture data retrieval methods and point out some still existing problems at the end.

Development of Basketball Assisted Training System Based on Kinect Motion Capture

2014 ◽  
Vol 926-930 ◽  
pp. 1318-1321
Author(s):  
Teng Da Li ◽  
Fang Wen
Keyword(s):  
Data Processing ◽  
Motion Capture ◽  
Three Dimensional ◽  
Training System ◽  
Motion Sensor ◽  
Technology Application ◽  
Motion Data ◽  
Time Performance ◽  
Object Technology ◽  
Capture Technique

Motion capture technique is motion data processed by a motion sensor and optical equipment tracker record computer. Three-dimensional information is to restore the moving object technology. Application of motion capture technology in sports training, the training into the scientific digital stage update the motion capture technology make it cheaper. The paper studied the technology of Kinect based motion capture, and its application in basketball training. This method has the advantages of simple data processing, high real-time performance and low price etc..

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.

Sign in / Sign up

Export Citation Format

Share Document