Optimal Camera Configuration for Large-Scale Motion Capture Systems
Xiongming Dai (louisiana state university),* Gerald Baumgartner (Louisiana State University)
The 34th British Machine Vision Conference
Abstract
Camera network designs and 3D marker-based motion capture systems are enabling high-quality real-time interaction for multiple users. For greater efficiency, the camera configuration is motivated by the need to achieve 3D realistic and dynamic effects. We convert each sensing requirement into the geometrical and optical constraints on sensor location, developing a binary integer programming model with an included occlusion culling factor, from which the 3D region of viewpoints that satisfies that constraint is computed by greedy heuristics with Riesz-particle scale optimization. The optimal camera configuration problem is $\mathcal{NP}$-hard. We prove that our performance ratio $H(k)$ grows at most logarithmically, under mild assumptions.Video
Citation
@inproceedings{Dai_2023_BMVC,
author = {Xiongming Dai and Gerald Baumgartner},
title = {Optimal Camera Configuration for Large-Scale Motion Capture Systems},
booktitle = {34th British Machine Vision Conference 2023, {BMVC} 2023, Aberdeen, UK, November 20-24, 2023},
publisher = {BMVA},
year = {2023},
url = {https://papers.bmvc2023.org/0448.pdf}
}
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