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Technical Brief

Development of a New Calibration Procedure and Its Experimental Validation Applied to a Human Motion Capture System

[+] Author and Article Information
Ana Cristina Royo Sánchez

Design and Manufacturing Engineering Department,
University of Zaragoza,
C/ María de Luna, 3 - Building: Torres Quevedo,
Zaragoza 50018, Spain
e-mail: crisroyo@unizar.es

Juan José Aguilar Martín, Jorge Santolaria Mazo

Design and Manufacturing Engineering Department,
University of Zaragoza,
C/ María de Luna, 3 - Building: Torres Quevedo,
Zaragoza 50018, Spain

Experimental validation is done with four or three cameras, as in the two cases studied in the spatial characterization [13,14]. In this paper, the results shown correspond to the four-camera experiments (the results with three cameras are similar).

Manuscript received March 25, 2014; final manuscript received September 2, 2014; accepted manuscript posted September 11, 2014; published online October 15, 2014. Assoc. Editor: Paul Rullkoetter.

J Biomech Eng 136(12), 124502 (Oct 15, 2014) (7 pages) Paper No: BIO-14-1135; doi: 10.1115/1.4028523 History: Received March 25, 2014; Revised September 02, 2014; Accepted September 11, 2014

Motion capture systems are often used for checking and analyzing human motion in biomechanical applications. It is important, in this context, that the systems provide the best possible accuracy. Among existing capture systems, optical systems are those with the highest accuracy. In this paper, the development of a new calibration procedure for optical human motion capture systems is presented. The performance and effectiveness of that new calibration procedure are also checked by experimental validation. The new calibration procedure consists of two stages. In the first stage, initial estimators of intrinsic and extrinsic parameters are sought. The camera calibration method used in this stage is the one proposed by Tsai. These parameters are determined from the camera characteristics, the spatial position of the camera, and the center of the capture volume. In the second stage, a simultaneous nonlinear optimization of all parameters is performed to identify the optimal values, which minimize the objective function. The objective function, in this case, minimizes two errors. The first error is the distance error between two markers placed in a wand. The second error is the error of position and orientation of the retroreflective markers of a static calibration object. The real co-ordinates of the two objects are calibrated in a co-ordinate measuring machine (CMM). The OrthoBio system is used to validate the new calibration procedure. Results are 90% lower than those from the previous calibration software and broadly comparable with results from a similarly configured Vicon system.

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Figures

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Fig. 3

Distances from the points found to the straight lines which point to the scene from the camera

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Fig. 4

Optimization algorithm schedule

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Fig. 2

Systems of world and camera reference

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Fig. 1

The camera model in the Tsai's calibration method

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Fig. 5

Floor plan of the static calibration object, the capture volume, and the OrthoBio cameras

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Fig. 6

Bar used in spatial characterization

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