Low-cost experimental apparatus for motion tracking based on image processing and camera calibration techniques

被引:4
作者
Amarante, Rodrigo M. [1 ]
Fujarra, Andre L. C. [2 ]
机构
[1] Univ Sao Paulo, Numer Offshore Tank, Butanta, SP, Brazil
[2] Univ Fed Santa Catarina, Joinville, SC, Brazil
来源
SN APPLIED SCIENCES | 2020年 / 2卷 / 09期
关键词
Tests monitoring; Flexible cable; Low cost; Camera calibration; Digital image processing;
D O I
10.1007/s42452-020-03268-y
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The present work focuses on the use of a low-cost equipment to monitor static and dynamic tests as an alternative to expensive commercial devices. First, we describe a procedure for cameras calibration and image processing in order to establish a less invasive (than other common instrumentation, such as strain gauges) and much cheaper motion capture method (than commercial tracking systems). Following, two cameras and one personal computer (with an image acquisition board) are used as the monitoring apparatus for tracking the movements of a flexible cable under harmonic excitation at its top end. The experimental results are then compared with numerical simulations, showing a fairly good agreement and the same level of precision as that obtained with one of the most used motion capture system in laboratories. The proposed experimental methodology correctly identifies the displacements, frequencies, and dynamic geometric behavior of the flexible model in all directions. Although commercial solutions are faster, since data processing and cameras calibration take place in real time, the acquisition cost of the suggested equipment is most affordable for small industries, educational institutions and projects with restrict budget on kinesiology, physiology, dentistry, facial recognition and mechanics, among others.
引用
收藏
页数:11
相关论文
共 24 条
[1]   Direct Linear Transformation from Comparator Coordinates into Object Space Coordinates in Close-Range Photogrammetry [J].
Abdel-Aziz, Y. I. ;
Karara, H. M. .
PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 2015, 81 (02) :103-107
[2]  
Amarante R M, 2015, THESIS
[3]  
Bernitsas M M, 1981, THESIS
[4]   DeepCalib: A Deep Learning Approach for Automatic Intrinsic Calibration of Wide Field-of-View Cameras [J].
Bogdan, Oleksandr ;
Eckstein, Viktor ;
Rameau, Francois ;
Bazin, Jean-Charles .
PROCEEDINGS CVMP 2018: THE 15TH ACM SIGGRAPH EUROPEAN CONFERENCE ON VISUAL MEDIA PRODUCTION, 2018,
[5]   A Computer-Vision Based Application for Student Behavior Monitoring in Classroom [J].
Bui Ngoc Anh ;
Ngo Tung Son ;
Phan Truong Lam ;
Le Phuong Chi ;
Nguyen Huu Tuan ;
Nguyen Cong Dat ;
Nguyen Huu Trung ;
Aftab, Muhammad Umar ;
Tran Van Dinh .
APPLIED SCIENCES-BASEL, 2019, 9 (22)
[6]  
Canedo Daniel, 2018, Highlights of Practical Applications of Agents, Multi-Agent Systems, and Complexity: The PAAMS Collection: International Workshops of PAAMS 2018. Communications in Computer and Information Science (887), P371, DOI 10.1007/978-3-319-94779-2_32
[7]   The Importance of Camera Calibration and Distortion Correction to Obtain Measurements with Video Surveillance Systems [J].
Cattaneo, C. ;
Mainetti, G. ;
Sala, R. .
XXII AIVELA ANNUAL MEETING, 2015, 658
[8]   Review of techniques for 2D camera calibration suitable for industrial vision systems [J].
D'Emilia, G. ;
Di Gasbarro, D. .
7TH YOUNG RESEARCHER MEETING, 2017, 841
[9]   Unmanned aerial vehicle-aided stereo camera calibration for outdoor applications [J].
Feng, Weiwu ;
Zhang, Shuiqiang ;
Liu, Haibo ;
Yu, Qifeng ;
Wu, Shen ;
Zhang, Dongsheng .
OPTICAL ENGINEERING, 2020, 59 (01)
[10]  
Gonzalez R.C., 2002, Digital Image Processing