||Nowadays, some gigantic models can be easily produced in many applications and their storage cost often exceeds the RAM size in a common workstation. The model simplification and the multiresolution techniques are a rather mature technologies that in many cases can efficiently manage complex data: however, the RAM size is often a severe bottleneck, even for high-performance graphics workstations. Thus, using an external memory technique is mandatory in this case: it is important to encode huge models in the most efficient way as possible, maintaining the opportunity to analyze, to manage and to display them according to the user requests and choices.
In this paper we define an extensible framework, called OMSM (short for Objects Management in Secondary Memory), for managing huge models: it supports external memory management of complex models, loading dynamically in RAM only the selected sections. All the functionalities implemented on this framework can be applied to a generic geometric model, independently from its dimension, on low-cost PC platforms.