Content-based 3-D Shape Retrieval for Pervasive Computing

3D models are a new kind of cross-media resource which can be frequently seen in the network. Since the amount of them is very huge now, content-based retrieval can help to recognize a certain object or retrieve similar ones from the giant database. This paper presents a new method for deriving 3D moment invariants and uses them as shape descriptors for the representation of 3D models. They are insensitive to surface noise and can be used in pervasive environment conveniently. We also illustrate how to build up experimental system and simulate 3D shape retrieval in wireless environment