With the growth in computing, storage, and networking infrastructure, it is becoming feasible for multimedia professionals, such as graphic designers in commercial, manufacturing, scientific, and entertainment areas, to work with 3D models of objects of their interest. As a result, the volume of 3D models available in digital form is rapidly growing. However, we lack a digital library system for these models, where they can be stored, searched and retrieved efficiently. As the size of data representing a 3D model is usually large, it presents a number of challenges in building an efficient digital library system. In this paper, we propose a digital library framework that is designed to provide storage services for 3D models, search and discovery services, and progressive retrieval services. The key to the digital library framework is a representation of a 3D model based on 'surface signatures'. This representation scheme captures the shape information of any free-form surface and encodes it into a 2D image corresponding to a certain point on the surface. The original object can be reconstructed from the intersection of the inverse mapping of few signatures with accuracy that depends on the location of the selected points and the number of signatures used in representing the object. This compressed representation allows for efficient storage and is amenable for progressive retrieval. Also, the 3-D objects can be checked for similarities in the compressed domain.
This paper introduces a new transform, called the signature transform, to concisely represent fee-from 3D objects. The signature transform is based on a free-form surface representation called the surface signature. The surface signature captures some information about a 3D surface, as viewed from a special point called the anchor, such as the curvature, distance from anchor point,....etc. The surface signature stores this information in the form of a 2D image called the surface signature image. The signature transform uses different variations of the surface signature as viewed from selected landmark points. The selection of anchor points is crucial to the success of the signature transform an approach for selecting landmark points based on curvature value will be presented. The signature transform can then be used as a form of a progressive compression of objects that will allow the view and manipulation of the 3D object even if all the compression data are not received. Unlike the previously existing progressive compression techniques, the signature transform does not require receiving the data in special order nor does it have key frames in the representation.