We describe a family of new imaging systems, called Argus eyes, that consist of common video cameras arranged in some network. The system we built consists of six cameras arranged so that they sample different parts of the visual sphere. This system has the capability of very accurately estimating its own 3D motion and consequently estimating shape models from the individual videos. The reason is that inherent ambiguities of confusion between translation and rotation disappear in this case. We provide an algorithm and several experiments using real outdoor or indoor images demonstrating the superiority of the new sensor with regard to 3D motion estimation.