TAXONOMY FOR 3D CONTENT-BASED OBJECT RETRIEVAL METHODS

Abstract

The use of three-dimensional (3D) image and model databases throughout the Internet is growing both in number and size. The emergence of 3D media is also directly related to the emergence of the 3D acquisition technologies. Indeed, recent advances in 3D scanner acquisition and 3D graphics rendering technologies boost the creation of 3D model archives for several application domains. Therefore, the development of efficient search mechanisms is required for the effective retrieval of 3D objects from large repositories. Over the last years, a large number of competing techniques have been developed for the purpose of content-based retrieval of 3D objects and consequently, more research is required to be conducted on surveying and comparing such proposed techniques. In this paper, we provide a comprehensive survey on the recent methods for content-based 3D object retrieval guided by a proposed taxonomy based on different shape descriptors. Finally, a performance comparison is carried out among selected methods based on qualitative measures.