This paper describes a method for learning the 2-D shapes of the objects from their sample image clips. We view an object as a congregation of a set of component parts with simple shapes. When presented with a sample image clip of an object, our learning system first detects the components of that object and saves the shape descriptions of those components in the object model. Next it determines the geometrical relationships between the components which are also saved in the object model as constraints. Finally, it generates a strategy for recognizing such an object. As we will show, our system can use this automatically extracted information to detect such an object in other scenes, even when the object is partially occluded.