The problem of surface reconstruction from stereo images for large scenes having large depth ranges is considered. The passive stereo paradigm is inadequate for this problem because of the need to aim cameras in different directions and to fixate on different objects. An active stereo approach, in which the scene is systematically scanned and an image acquisition and surface reconstruction are integrated using a four-step process, is presented. First, a new fixation point is selected from among the nonfixated, low-resolution scene parts of current fixation. Then a reconfiguration of cameras is initiated for refixation. As reconfiguration progresses, the images of the new fixation point gradually deblur and the accuracy of the stereo estimate of the point improves. The improved stereo estimate is used to achieve accurate focus and vergence settings of the cameras for fixation. Finally, focus-based depth estimates are obtained at a grid near the fixation point whose density is determined by the local surface slope. These estimates are fused with those obtained from stereo using maximum likelihood (weighted averaging), and the interpolated values at nongrid points of the difference between the estimates at grid points are used to update the stereo estimates at nongrid points.