基于实时视频的三维事件重建摄像机网络的同步与标定

Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops Pub Date : 2005-06-20 DOI:10.1109/CVPR.2005.338

Sudipta N. Sinha, M. Pollefeys

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引用次数: 5

摘要

我们提出了一种使用多个摄像机从不同视点记录动态事件的自动重建方法。我们的方法通过分析多个视频流中轮廓的运动来恢复所有必要的信息。第一步是计算相机对的标定和同步。我们使用一种高效的基于ransac的算法来计算时间偏移和外极几何，以搜索外极以及鲁棒性。在接下来的阶段，恢复整个相机网络的校准和同步，然后通过最大似然估计进行细化。最后，利用视觉船体算法恢复被观测物体的动态形状。

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Synchronization and Calibration of a Camera Network for 3D Event Reconstruction from Live Video

We present an approach for automatic reconstruction of a dynamic event using multiple video cameras recording from different viewpoints. Our approach recovers all the necessary information by analyzing the motion of the silhouettes in the multiple video streams. The first step consists of computing the calibration and synchronization for pairs of cameras. We compute the temporal offset and epipolar geometry using an efficient RANSAC-based algorithm to search for the epipoles as well as for robustness. In the next stage the calibration and synchronization for the complete camera network is recovered and then refined through maximum likelihood estimation. Finally, a visual hull algorithm is used to the recover the dynamic shape of the observed object.

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Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops

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