The central requirement in the bin-of-parts problem is to direct a robot manipulator to select, grasp, and remove an arbitrarily-oriented part (or object) from a bin of many such objects. This necessitates the estimation of the pose (position and orientation) of a partially-occluded object and, in general, its 3-D structure. The solution of such a problem using passive vision requires the use of sophisticated processing incorporating multiple redundant representations, such as stereopsis, motion, and analysis of object shading. This paper describes the first step is such an approach, that of determining a depth-map of the bin-of-parts, using optical flow derived from camera motion. Since the robotics environment is naturally constrained, simple camera motion can be generated by mounting the camera on the robot end-effector and directing the effector along a known path: the simplest motion, along the optical axis, is utilised in this case. For motion along the optical axis, the rotational components of flow are nil and the direction of the translational components is effectively radial from the fixation point (on the optical axis). Hence, it remains only to determine the magnitude of the velocity vector. Optical flow is estimated by computing the time derivative of a sequence of images, i.e., by forming differences between two successive images and, in particular, of contours in images which have been generated from the zero-crossings of Laplacian of Gaussian-filtered images. Once the flow field has been determined, a depth map is computed, initially for all contour points in the image, and ultimately for all surface points by interpolation.