In this paper we present an automatic method for calibrating a network of cameras from only silhouettes. This is particularly useful for shape-from-silhouette or visual-hull systems, as no additional data is needed for calibration. The key novel contribution of this work is an algorithm to robustly compute the epipolar geometry from dynamic silhouettes. We use the fundamental matrices computed by this method to determine the projective reconstruction of the complete camera configuration. This is refined into a metric reconstruction using self-calibration. We validate our approach by calibrating a four camera visual-hull system from archive data where the dynamic object is a moving person. Once the calibration parameters have been computed, we use a visual-hull algorithm to reconstruct the dynamic object from its silhouettes.<\/p>\n","protected":false},"excerpt":{"rendered":"
In this paper we present an automatic method for calibrating a network of cameras from only silhouettes. This is particularly useful for shape-from-silhouette or visual-hull systems, as no additional data is needed for calibration. The key novel contribution of this work is an algorithm to robustly compute the epipolar geometry from dynamic silhouettes. 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