When using optical motion capture systems, increasing the number of cameras improves the visibility. However, the software used to deal with the information fusion from multiple cameras may compromise the accuracy of the system due to camera dropout, which can vary with time. In cadaver studies of radial head motion, increasing the number of cameras used by the motion capture system seemed to decrease the accuracy of the measurements. This study investigates the cause. The hypothesis was that errors in position can be induced when markers are obscured from and then restored to a camera’s viewable range, as can happen in biomechanical studies. Accuracy studies quantified the capabilities of the motion capture system with precision translation and rotation movements. To illustrate the effect that abrupt perceived changes in a marker’s position can have on the calculation of radial head travel, simulated motion experiments were performed. In these studies, random noise was added to simulated data, which obscured the resultant path of motion. Finally, camera-blocking experiments were performed in which precise movements were measured with a six-camera Vicon system and the errors between the actual and perceived motion were computed. During measurement, cameras were selectively blocked and restored to view. The maximum errors in translation and rotation were 3.7 mm and 0.837 deg, respectively. Repeated measures analysis of variance (ANOVAs) (α=0.05) confirmed that the camera-blocking influenced the results. Taken together, these results indicate that camera-switching can affect the observation of fine movements using a motion analysis system with a large number of cameras. One solution is to offer opportunity for user interaction in the software to choose the cameras used for each instant of time.

1.
Abu-Faraj
,
Z. O.
,
Gautam Sampath
,
B. S.
,
Smith
,
P. A.
, and
Harris
,
G. F.
, 1997, “
A Clinical System for the Analysis of Three-Dimensional Pediatric Foot and Ankle Motion
,”
Proceedings of the 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
, pp.
1831
1834
.
2.
Kepple
,
T. M.
,
Stanhope
,
S. J.
, and
Rich
,
A. H.
, 1988, “
The Presentation and Evaluation of a Video Based, Six Degree-of-Freedom Approach for Analyzing Human Motion
,”
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society
, pp.
649
650
.
3.
Sampath
,
G.
,
Abu-Faraj
,
Z. O.
,
Smith
,
P. A.
, and
Harris
,
G. F.
, 1998, “
Design and Development of an Active Marker Based System for Analysis of 3-D Pediatric Foot and Ankle Motion
,”
Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
, pp.
2415
2417
.
4.
Maletsky
,
L. P.
, and
Hillberry
,
B. M.
, 2005, “
Simulating Dynamic Activities Using a Five-Axis Knee Simulator
,”
ASME J. Biomech. Eng.
0148-0731,
127
(
1
), pp.
123
133
.
5.
Liu
,
H.
,
Holt
,
C.
, and
Evans
,
S.
, 2007, “
Accuracy and Repeatability of an Optical Motion Analysis System for Measuring Small Deformations of Biological Tissues
,”
J. Biomech.
,
40
(
1
), pp.
210
214
. 0021-9290
6.
Chiari
,
L.
,
Della Croce
,
U.
,
Leardini
,
A.
, and
Cappozzo
,
A.
, 2005, “
Human Movement Analysis Using Stereophotogrammetry. Part 2: Instrumental Errors
,”
Gait and Posture
,
21
(
2
), pp.
197
211
. 0966-6362
7.
Figueroa
,
P. J.
,
Leite
,
N. J.
, and
Barros
,
R. M.
, 2003, “
A Flexible Software for Tracking of Markers Used in Human Motion Analysis
,”
Comput. Methods Programs Biomed.
,
72
(
2
), pp.
155
165
. 0169-2607
8.
Mühlich
,
M.
, 1998, “
The Role of Total Least Squares in Motion Analysis
,”
Computer Vision—ECCV 1998
(
Lecture Notes in Computer Science
),
Springer
,
Berlin
, p.
305
.
9.
Pribanic
,
T.
,
Sturm
,
P.
, and
Cifrek
,
M.
, 2005, “
Camera Parameter Initialization for 3D Kinematic Systems
,”
Proceedings of the Fourth International Symposium on Image and Signal Processing and Analysis
, pp.
494
499
.
10.
Malis
,
E.
, and
Bartoli
,
A.
, 2004, “
Euclidean Reconstruction Independent on Camera Intrinsic Parameters
,”
Proceedings of the 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems
, pp.
2313
2318
.
11.
Unal
,
G.
, and
Yezzi
,
A.
, 2004, “
A Variational Approach to Problems in Calibration of Multiple Cameras
,”
Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
, pp.
I
-172–
178
.
12.
Richards
,
J. G.
, 1999, “
The Measurement of Human Motion: A Comparison of Commercially Available Systems
,”
Hum. Mov. Sci.
0167-9457,
18
(
5
), pp.
589
602
.
13.
Stein
,
G. P.
, 1995, “
Accurate Internal Camera Calibration Using Rotation, With Analysis of Sources of Error
,”
Proceedings of the Fifth International Conference on Computer Vision
, pp.
230
236
.
14.
Miller
,
C.
,
Mulavara
,
A.
, and
Bloomberg
,
J.
, 2002, “
A Quasi-Static Method for Determining the Characteristics of a Motion Capture Camera System in a “Split-Volume” Configuration
,”
Gait and Posture
,
16
(
3
), pp.
283
287
. 0966-6362
15.
Chen
,
Q.
,
Lazennec
,
J. Y.
,
Guyen
,
O.
,
Kinbrum
,
A.
,
Berry
,
D. J.
, and
An
,
K. N.
, 2005, “
Technical Note: Validation of a Motion Analysis System for Measuring the Relative Motion of the Intermediate Component of a Tripolar Total Hip Arthroplasty Prosthesis
,”
Med. Eng. Phys.
,
27
(
6
), pp.
505
512
. 1350-4533
16.
Florou
,
G.
, and
Mohr
,
R.
, 1996, “
What Accuracy for 3D Measurements With Cameras?
Proceedings of the 13th International Conference on Pattern Recognition
, pp.
354
358
.
17.
Maletsky
,
L. P.
,
Sun
,
J.
, and
Morton
,
N. A.
, 2007, “
Accuracy of an Optical Active-Marker System to Track the Relative Motion of Rigid Bodies
,”
J. Biomech.
,
40
(
3
), pp.
682
685
. 0021-9290
18.
Cappozzo
,
A.
,
Catani
,
F.
,
Leardini
,
A.
,
Benedetti
,
M. G.
, and
Croce
,
U. D.
, 1996, “
Position and Orientation in Space of Bones During Movement: Experimental Artefacts
,”
Clin. Biomech. (Bristol, Avon)
,
11
(
2
), pp.
90
100
. 0268-0033
19.
Cappozzo
,
A.
,
Cappello
,
A.
,
Croce
,
U. D.
, and
Pensalfini
,
F.
, 1997, “
Surface-Marker Cluster Design Criteria for 3-D Bone Movement Reconstruction
,”
IEEE Trans. Biomed. Eng.
0018-9294,
44
(
12
), pp.
1165
1174
.
20.
Ehara
,
Y.
,
Fujimoto
,
H.
,
Miyazaki
,
S.
,
Tanaka
,
S.
, and
Yamamoto
,
S.
, 1995, “
Comparison of the Performance of 3D Camera Systems
,”
Gait and Posture
,
3
(
3
), pp.
166
169
. 0966-6362
21.
Ehara
,
Y.
,
Fujimoto
,
H.
,
Miyazaki
,
S.
,
Mochimaru
,
M.
,
Tanaka
,
S.
, and
Yamamoto
,
S.
, 1997, “
Comparison of the Performance of 3D Camera Systems II
,”
Gait and Posture
,
5
(
3
), pp.
251
255
. 0966-6362
22.
Kaucic
,
R.
,
Amitha Perera
,
A. G.
,
Brooksby
,
G.
,
Kaufhold
,
J.
, and
Hoogs
,
A.
, 2005, “
A Unified Framework for Tracking Through Occlusions and Across Sensor Gaps
,”
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
, pp.
990
997
.
23.
Dockstader
,
S. L.
, and
Tekalp
,
A. M.
, 2001, “
Multiple Camera Tracking of Interacting and Occluded Human Motion
,”
Proc. IEEE
0018-9219,
89
(
10
), pp.
1441
1455
.
24.
Yamane
,
K.
,
Kuroda
,
T.
, and
Nakamura
,
Y.
, 2004, “
High-Precision and High-Speed Motion Capture Combining Heterogeneous Cameras
,”
Proceedings of the International Conference on Intelligent Robots and Systems
, pp.
279
286
.
25.
Cai
,
Q.
, and
Aggarwal
,
J. K.
, 1998, “
Automatic Tracking of Human Motion in Indoor Scenes Across Multiple Synchronized Video Streams
,”
Proceedings of the Sixth International Conference on Computer Vision
, pp.
356
362
.
26.
Cai
,
Q.
, and
Aggarwal
,
J. K.
, 1999, “
Tracking Human Motion in Structured Environments Using a Distributed-Camera System
,”
IEEE Trans. Pattern Anal. Mach. Intell.
0162-8828,
21
(
11
), pp.
1241
1247
.
27.
Borghese
,
N.
, and
Prigiroli
,
P.
, 2002, “
Tracking Densely Moving Markers
,”
Proceedings of the IEEE 3D Processing Visualization and Transmission
, pp.
682
685
.
28.
Gleicher
,
M.
, 2001, “
Comparing Constraint-Based Motion Editing Methods
,”
Graphical Models
,
63
(
2
), pp.
107
134
. 1524-0703
29.
Gleicher
,
M.
, and
Ferrier
,
N.
, 2002, “
Evaluating Video-Based Motion Capture
,”
Proceedings of the Computer Animation 2002
, pp.
75
80
.
30.
Kopparapu
,
S.
, and
Corke
,
P.
, 2001, “
The Effect of Noise on Camera Calibration Parameters
,”
Graphical Models
,
63
(
5
), pp.
277
303
. 1524-0703
31.
Butler
,
A. L.
,
Miller
,
M. C.
,
Galik
,
K.
, and
Baratz
,
M. E.
, 2005, “
Translational Kinematics of the Radial Head Before and After Radial Head Replacement
,”
Annual Meeting of the American Society for Surgery of the Hand
, San Antonio, TX.
32.
Miller
,
M. C.
,
Galik
,
K.
,
Dazen
,
D.
,
DeMeo
,
P.
, and
Baratz
,
M. E.
, 2005, “
The Effect of Annular Ligament Resection of Radial Head Kinematics
,”
ASME Bioengineering
, Vail, CO.
33.
Galik
,
K.
,
Baratz
,
M. E.
,
Butler
,
A. L.
,
Dougherty
,
J.
,
Cohen
,
M. S.
, and
Miller
,
M. C.
, 2007, “
The Effect of the Annular Ligament on Kinematics of the Radial Head
,”
J. Hand Surg. [Am]
,
32
(
8
), pp.
1218
1224
. 0363-5023
34.
Welk
,
M.
,
Weickert
,
J.
,
Becker
,
F.
,
Schnorr
,
C.
,
Feddern
,
C.
, and
Burgeth
,
B.
, 2007, “
Median and Related Local Filters for Tensor-Valued Images
,”
Signal Process.
,
87
(
2
), pp.
291
308
. 0165-1684
35.
See EPAPS Document No. E-JBENDY-130-011806 for supplement table. For more information on EPAPS, see http://www.aip.org/pubservs/epaps.htmlhttp://www.aip.org/pubservs/epaps.html.
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