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Optimal camera placement for motion capture systems in the presence of dynamic occlusion
Conference proceeding   Open access

Optimal camera placement for motion capture systems in the presence of dynamic occlusion

Pooya Rahimian and Joseph Kearney
Proceedings of the 21st ACM Symposium on virtual reality software and technology, Vol.13-15-, pp.129-138
VRST '15
11/13/2015
DOI: 10.1145/2821592.2821596
url
https://doi.org/10.1145/2821592.2821596View
Published (Version of record) Open Access

Abstract

Optical motion capture is based on estimating the three-dimensional positions of markers by triangulation from multiple cameras. Successful performance depends on points being visible from at least two cameras and on the accuracy of the triangulation. Triangulation accuracy is strongly related to the positions and orientations of the cameras. Thus, the configuration of the camera network has a critical impact on performance. A poor camera configuration may result in a low quality three-dimensional (3D) estimation and consequently low quality of tracking. This paper proposes a camera configuration metric that is based on a probabilistic model of target point visibility from cameras with "good" views. An efficient algorithm, based on simulated annealing, is introduced for estimating the optimal configuration of an arbitrary set of cameras for a given distribution of target points. The accuracy and robustness of the algorithm are evaluated through both simulation and empirical measurement. An implementation of the method is available for download as a tool for the community [Rahimian and Kearney 2015] (Figure 1).
 Augmented Reality Virtual Reality camera placement CAVE dynamic occlusion motion capture

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