  Metric auto calibration of a camera network from multiple views has been
reported by several authors. Resulting 3D reconstruction recovers shape
faithfully, but not scale. However, preservation of scale becomes critical in
applications, such as multi-party telepresence, where multiple 3D scenes need
to be fused into a single coordinate system. In this context, we propose a
camera network configuration that includes a stereo pair with known baseline
separation, and analytically demonstrate Euclidean auto calibration of such
network under mild conditions. Further, we experimentally validate our theory
using a four-camera network. Importantly, our method not only recovers scale,
but also compares favorably with the well known Zhang and Pollefeys methods in
terms of shape recovery.
