We present an approach for automatic reconstruction of a dynamic event using multiple video cameras recording from different viewpoints. Those cameras do not need to be calibrated or even synchronized. 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. For unsynchronized video streams silhouettes are interpolated to deal with subframe temporal offsets. We demonstrate the validity of our approach by obtaining the calibration, synchronization and 3D reconstruction of a moving person from a set of 4 minute videos recorded from 4 widely separated video cameras.