**7. References**


**26** 

*Belgium* 

**Optimized Scalable Wavelet-Based** 

Shahid M. Satti, Leon Denis, Ruxandra Florea,

*Department of Electronics and Informatics (ETRO)* 

*Vrije Universiteit Brussel-IBBT, Brussels,* 

Jan Cornelis, Peter Schelkens and Adrian Munteanu

**Codec Designs for Semi-Regular 3D Meshes** 

3D graphics applications make use of polygonal 3D meshes for object's shape representation. The recent introduction of high-performance laser scanners and fast microcomputer systems gave rise to high-definition graphics applications. In such applications, objects with complex textures are represented using dense 3D meshes which consist of hundreds of thousands of vertices. Due to their enormous data size, such highlydetailed 3D meshes are rather intricate to store, costly to transmit via bandwidth-limited transmission media, and hard to display on end-user terminals with diverse display capabilities. Scalable compression, wherein the source representation can be adapted to the users' requests, available bandwidth and computational capabilities, is thus of paramount importance in order to make efficient use of the available resources to process, store and

State-of-the-art scalable mesh compression systems can be divided into two main categories. A first category includes codecs that directly compress the irregular topology meshes in the spatial domain. In such codecs, the connectivity information is encoded losslessly while mesh simplification methods such as vertex coalescing (Rossignac & Borrel, 1993), edge decimation (Soucy & Laurendeau, 1996) and edge collapsing (Ronfard & Rossignac, 1996) are employed to encode geometry. These mesh simplification methods progressively remove those mesh vertices which yield the smallest distortion. In order to enable the reconstruction of the original mesh at various levels of detail (LODs), the discarded vertices are encoded in the compressed bit-stream. Mesh compression systems belonging to this category include Progressive Meshes (Li & Kuo, 1998), (Pajarola & Rossignac, 2000) and Topological Surgery (Taubin et al., 1998). These techniques generally exhibit two major drawbacks: first, due to the highly irregular topology of the input mesh, a large source rate is needed for lossless encoding of connectivity. Secondly, encoding the removed vertices in the compressed bit-stream is quite costly for highresolution meshes. Therefore, such schemes are not useful for complex meshes containing a large number of vertices. An alternative that solves the problem of the large source rates needed to encode the connectivity information, described above, is remeshing, which can be used to convert the original irregular mesh into a mesh consisting of regular elements, such as B-spline (Eck & Hoppe, 1996) or subdivision connectivity patches (Eck et al., 1995). The regular

**1. Introduction** 

transmit high-resolution meshes.

