In order for a mobile robot to acquire a shape model of an unknown object, it must be able to view the entire exterior of the object. However, in an unstructured environment, it is impossible to know the extent to which the robot can circumnavigate the object. If the entire object cannot be seen, then it is impractical to discuss creating object models which contain only viewable object surfaces. In fact, it is easy to conceive if an object which possesses exterior surfaces that are hidden from any reasonable viewpoint. However, it is generally possible to establish limits to the volume of space that the object can occupy. Such a volume represents the combination of space occluded from view with space actually taken up by the object. A model of this volume is valuable, in that it has the advantage of being a complete, enclosed boundary description. Object recognition routines, for example, may require complete boundary descriptions to work with. Even if complete boundary descriptions are not required, knowing the maximum possible extent of the object could prove valuable, perhaps in differentiating between several partial object model matches. Processing a single view, we build an ''OPUS'' (object plus unseen space) by combining ''object surfaces''--defining the fraction of the exterior of the object that can actually be seen--with ''occlusion surfaces''-- indicating the limits to the volume of space which is occluded from view.