streaming 3d meshes using spectral geometry images
The transmission of 3D models in the form of Geometry Images (GI) is an emerging and appealing concept due to the reduction in complexity from R 3 to image space and wide availability of mature image processing tools and standards. However, geometry images often suffer from the artifacts and error during compression and transmission. Thus, there is a need to address the artifact reduction, error resilience and protection of such data information during the transmission across an error prone network. In this paper, we introduce a new concept, called Spectral Geometry Images (SGI) , which naturally combines the powerful spectral analysis with geometry images. We show that SGI is more effective than GI to generate visually pleasing shapes at high compression rates. Furthermore, by coupling SGI to the proposed error protection scheme, we are able to ensure the smooth delivery of 3D model across error networks for different packet loss rate simulated using the two-state Markov model.
streaming 3d meshes geometry image transmission error resilience spectral analysis conformal parameterization image compression