Zhouyi WANG,Weijia ZONG,Bingcheng WANG,et al.The Marking Technology in Motion Capture for the Complex Locomotor Behavior of Flexible Small Animals (Gekko gecko)[J].Asian Herpetological Research(AHR),2019,10(3):197-210.[doi:10.16373/j.cnki.ahr.180071]
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The Marking Technology in Motion Capture for the Complex Locomotor Behavior of Flexible Small Animals (Gekko gecko)
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Asian Herpetological Research[ISSN:2095-0357/CN:51-1735/Q]

Issue:
2019 VoI.10 No.3
Page:
197-210
Research Field:
Publishing date:
2019-09-23

Info

Title:
The Marking Technology in Motion Capture for the Complex Locomotor Behavior of Flexible Small Animals (Gekko gecko)
Author(s):
Zhouyi WANG1*#;  Weijia ZONG1#;  Bingcheng WANG1;  Junjie ZHU2;  Kai QIN2 and Zhendong DAI1*
1 Institute of Bio-inspired Structure and Surface Engineering, Nanjing University of Aeronautics and Astronautics, 29 Yudao Street, Nanjing 210016, Jiangsu, China
2 Shanghai Institute of Aerospace System Engineering, 3888 Yuanjiang Road, Shanghai 201109, China
Keywords:
small flexible animals;  marking technology;  motion capture;  quantification of locomotor behavior;  gecko
PACS:
-
DOI:
10.16373/j.cnki.ahr.180071
Abstract:
Animals have evolved a variety of behavior patterns to adapt to the environment. Motion-capture technology is utilized to quantify and characterize locomotor behaviors to reveal the mechanisms of animal motion. In the capture of flexible, small animals with complex locomotor behaviors, the markers interfere with each other easily, and the motion forms (bending, twisting) of the moving parts are obviously different; thus, it is a great challenge to realize accurate quantitative characterization of complex locomotor behaviors. The correlation between the marker properties, including the size and space length, and the precision of the system are revealed in this paper, and the effects of diverse marker shapes on the capturing accuracy of the captured objects in different motion forms were tested. Results showed that the precision of system is significantly improved when the ratio of the space length to the diameter of the markers is larger than four; for the capture of the spatial twisting motion of the flexible object, the hexagon markers had the lowest spatial lost-marker rate relative to the circle, triangle, and square. Customized markers were used to capture the locomotor behavior of the gecko-inspired robot (rigid connection) and the gecko (flexible connection). The results showed that this marking technology can achieve high accuracy of motion capture for geckos (the average deviation was approximately 0.32 mm, and the average deviation’s variation rate was approximately 0.96%). In this paper, the marking technology for the motion capture of flexible, small animals with complex motion is proposed; it can effectively improve the system precision as well as the capture accuracy, and realize the quantitative characterization of the complex motion of flexible, small objects. It provides a reliable technical means to deeply study the evolution of the motion function of small animals and advance systematic research of motion-capture technology.

References:

Alexanderson S., O Sullivan C., Beskow J. 2017. Real-Time Labeling of Non-Rigid Motion Capture Marker Sets. Comput Graph, 69
Book W. J. 1984. Recursive Lagrangian Dynamics of Flexible Manipulator Arms. Int J Robot Res, 3(3): 87–101
Carse B., Meadows B., Bowers R., Rowe P. 2013. Affordable clinical gait analysis: An assessment of the marker tracking accuracy of a new low-cost optical 3D motion analysis system. Physiotherapy, 99(4): 347
Dai Z., Wang Z., Ji A. 2011. Dynamics of gecko locomotion: a force-measuring array to measure 3D reaction forces. J Exp Biol, 214(Pt 5): 703
Deetjen M. E., Biewener A. A., Lentink D. 2017. High-speed surface reconstruction of a flying bird using structured-light. J Exp Biol, 220(Pt 11): 1956
Dickinson M. H., Farley C. T., Full R. J., Koehl M. A. R., Kram R., Lehman S. 2000. How animals move: An integrative view. Science, 288(5463): 100
Eichelberger P., Ferraro M., Minder U., Denton T., Blasimann A., Krause F., Baur H. 2016. Analysis of accuracy in optical motion capture—A protocol for laboratory setup evaluation. J Biomech, 49(10): 2085–2088
Fan G., Zhang X. 2011. Video-Based Human Motion Estimation by?Part-Whole Gait Manifold Learning. London: Springer, 215–261.
Gleicher M. 1999. Animation from observation: Motion capture and motion editing. Acm Siggraph Comput Graph, 33(4): 51–54
G?pfert B., Krol Z., Freslier M., Krieg A. H. 2011. 3D video-based deformation measurement of the pelvis bone under dynamic cyclic loading. BioMed Eng OnLine, 10(1): 60
Hedrick T. 2008. Software techniques for two- and three-dimensional kinematic measurements of biological and biomimetic systems. Bioinspir Biomim, 3(3): 34001
Heikkila J., Silvén O. 2002. A four-step camera calibration procedure with implicit image correction, 1106–1112
Hoyt D. F., Taylor C. R. 1981. Gait and the energetic of locomotion in horses. Nature, 292(5820): 239–240
Huang B. 2004. Sequence Frame-based Optical Motion Capture System and Its Real iza tion. Comput Eng Appl, 40(17): 36–39
Hutchinson J. R., Schwerda D., Famini D. J., Dale R. H., Fischer M. S., Kram R. 2006. The locomotor kinematics of Asian and African elephants: changes with speed and size. J Exp Biol, 209(19): 3812–3827
Jr L. V. 2003. An Experiment Comparing Double Exponential Smoothing and Kalman Filter-Based Predictive Tracking Algorithms, 283
Li L. J., Yue X. L., Li Z. H., Jiang L., Cao C. G. 2008. A New Method for Camera Composition. Comput Sci, 35(2): 211–215
Luo Z. X., Zhuang Y. T., Pan Y. H., Liu F. 2002. Video Based Motion Capture. J Image Graph, 7(8): 752–758.
Medina-Carnicer R., Garrido-Castro J. L., Collantes-Estevez E., Martinez-Galisteo A. 2009. Fast detection of marker pixels in video-based motion capture systems. Pattern Recogn Lett, 30(4): 432–439
Menache A. 1999. Understanding motion capture for computer animation and video games. San Mateo, CA: Morgan Kaufmann Publishers Inc
Miller C., Mulavara A., Bloomberg J. 2002. A quasi-static method for determining the characteristics of a motion capture camera system in a “split-volume” configuration. Gait Posture, 16(3): 283–287
Miller L. A. 2017. Biomechanics: The aerodynamics buzz from mosquitoes. Nature, 40–42
Mittal A., Davis L. S. 2004. Visibility Analysis and Sensor Planning in Dynamic Environments, 175–189
Qin H. U., Wang W. Z., Xia S. H., Liu R. R., Jin-Tao L. I. 2008. Human Gait Tracking Method Based on Multiple Cameras. Comput Eng, 34(22): 220–222
Richards J. G. 1999. The measurement of human motion: A comparison of commercially available systems. Hum Movement Sci, 18(5): 589–602
Schavemaker J. G. M., Reinders M. J. T., Gerbrands J. J., Backer E. 2001. Image sharpening by morphological filtering. Pattern Recogn, 33(6): 997–1012
Sheng W. U., Zhang Q., Xiao B. X., Wei X. P. 2009. New approach of capture data processing for optical motion. Appl Res Comput, 26(5): 1937–1938
Sifakis E., Neverov I., Fedkiw R. 2005. Automatic determination of facial muscle activations from sparse motion capture marker data. ACM T Graph, 24(3): 417–425
Smith B. K. 1997. The effects of marker size on the accuracy of the Ariel Performance Analysis System [microform]
Surer E., Cereatti A., Grosso E., Della C. U. 2011. A markerless estimation of the ankle-foot complex 2D kinematics during stance. Gait Posture, 33(4): 532–537
Wang L., Wu F. C., Hu Z. Y. 2007. Multi-Camera Calibration with One-Dimensional Object under General Motions, 1–7
Wang W., Ji A., Manoonpong P., Shen H., Hu J., Dai Z., Yu Z. 2018. Lateral undulation of the flexible spine of sprawling posture vertebrates. J Comp Physiol A, 204(8): 707–719
Wang Z., Dai Z., Ji A., Ren L., Xing Q., Dai L. 2015a. Biomechanics of gecko locomotion: the patterns of reaction forces on inverted, vertical and horizontal substrates. Bioinspir Biomim, 10(1): 16019
Wang Z., Dai Z., Li W., Ji A., Wang W. 2015b. How do the substrate reaction forces acting on a gecko’s limbs respond to inclines? Naturwissenschaften, 102(1–2): 7
Webb P. W. 1984. Form and Function in Fish Swimming. Sci Am, 251(1): 72–82
Windolf M., G?tzen N., Morlock M. 2008. Systematic accuracy and precision analysis of video motion capturing systems—Exemplified on the Vicon-460 system. J Biomech, 41(12): 2776–2780
Xiang Z. R., Zhi J. Y., Bo-Chu X. U., Juan L. I. 2013. Survey on motion capture technique and its applications. Appl Res Comput, 30(8): 2241–2245
Yuan J. G., Zhang Y. N., Zheng J. B., Run-Ping X. I. 2009. Multi-Camera Layout Optimization Method for Motion Capture System. Microprocessors, 2009-03
Zheng L., Hedrick T. L., Mittal R. 2013. A multi-fidelity modelling approach for evaluation and optimization of wing stroke aerodynamics in flapping flight. J Fluid Mech, 721(4): 118–154
Zong W., Wang Z., Xing Q., Zhu J., Wang L., Qin K., Bai H., Yu M., Dai Z. 2018. The Method of Multi-Camera Layout in Motion Capture System for Diverse Small Animals. Appl Sci, 8(9):1562–1581

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Last Update: 2019-09-25