This paper presents a method of computing camera positions from a sequence of overlapping images obtained from a binocular/trinocular camera head. First, we find matching features among the images at each camera he ad position. Because the individual cameras are calibrated we can directly compute the 3D coordinates of these features using triangulation. Then we find matching features across adjacent images in the camera sequence. We compute the fundamental matrix between image pairs, and then the trilinear tensor between image triplets. The corresponding features that support the overlapping trilinear tensors are very reliable. Some of these matching features across the image sequence are also matching features among the images at each camera he ad location. This creates a potential set of matching 3D features between the adjacent images in the sequence. We compute the transformation between the camera positions in the image sequence using these matching 3D feature coordinates. Using multiple cameras has a number of advantages over computing the camera positions from a single camera. We directly obtain a Euclidean reconstruction of the camera path, we can reliably process very small motions, and there are no motion degeneracies.