Abstract

This paper presents a novel framework for view-dependent streaming of multiresolution meshes. In contrast to conventional progressive streaming in which the resolution of a model changes globally, our server dynamically adjusts the transmission order of the detail data with respect to the client's current viewpoint. By extending the truly selective refinement scheme for progressive meshes to a client-server architecture, we accomplish an efficient view-dependent streaming framework that minimizes network communication overhead to facilitate minimal latency of mesh updates for varying viewpoints. Furthermore, we reduce the per-client session data on the server side by using a special data structure for encoding which vertices have already been transmitted to each client. We provide an analytic comparison of several view-dependent streaming frameworks and show that our framework outperforms others in terms of the network overhead. Experimental results indicate that our framework is efficient enough for a broadcast scenario where one server streams geometry data to multiple clients with different view points.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call