This paper describes an imagingsystem that has been designed specifically for the purpose of recovering egomotion and structure from video. The system consists of six cameras in a network arranged so that they sample different parts of the visual sphere. This geometric configuration has provable advantages compared tosmall field of view cameras for the estimation of the system's own motion and consequently the estimationof shape models from the individual cameras. The reason is that inherent ambiguitiesof confusionbetween translation and rotation disappear. We provide algorithms for the calibration of the system and the 3D motion estimation. The calibrationis based on a new geometric constraint that relates the images of lines parallel in space to the rotation between the cameras. The 3D motion estimation uses a constraint relating structure directly to image gradients.