Robust object tracking techniques for vision-based 3D motion analysis applications

Vladimir A. Knyaz; Sergey Yu. Zheltov; Boris V. Vishnyakov

doi:10.1117/12.2227879

29 April 2016 Robust object tracking techniques for vision-based 3D motion analysis applications

Vladimir A. Knyaz, Sergey Yu. Zheltov, Boris V. Vishnyakov

Proceedings Volume 9896, Optics, Photonics and Digital Technologies for Imaging Applications IV; 98961D (2016) https://doi.org/10.1117/12.2227879
Event: SPIE Photonics Europe, 2016, Brussels, Belgium

Abstract

Automated and accurate spatial motion capturing of an object is necessary for a wide variety of applications including industry and science, virtual reality and movie, medicine and sports. For the most part of applications a reliability and an accuracy of the data obtained as well as convenience for a user are the main characteristics defining the quality of the motion capture system. Among the existing systems for 3D data acquisition, based on different physical principles (accelerometry, magnetometry, time-of-flight, vision-based), optical motion capture systems have a set of advantages such as high speed of acquisition, potential for high accuracy and automation based on advanced image processing algorithms. For vision-based motion capture accurate and robust object features detecting and tracking through the video sequence are the key elements along with a level of automation of capturing process. So for providing high accuracy of obtained spatial data the developed vision-based motion capture system “Mosca” is based on photogrammetric principles of 3D measurements and supports high speed image acquisition in synchronized mode. It includes from 2 to 4 technical vision cameras for capturing video sequences of object motion. The original camera calibration and external orientation procedures provide the basis for high accuracy of 3D measurements. A set of algorithms as for detecting, identifying and tracking of similar targets, so for marker-less object motion capture is developed and tested. The results of algorithms’ evaluation show high robustness and high reliability for various motion analysis tasks in technical and biomechanics applications.

Citation Download Citation

Vladimir A. Knyaz, Sergey Yu. Zheltov, and Boris V. Vishnyakov "Robust object tracking techniques for vision-based 3D motion analysis applications", Proc. SPIE 9896, Optics, Photonics and Digital Technologies for Imaging Applications IV, 98961D (29 April 2016); https://doi.org/10.1117/12.2227879

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