Cheng, I. and Boulanger, P. (2005). Feature Extraction on 3D TexMesh Using Scale-space Analysis and Perceptual Evaluation. IEEE Transactions on Circuits and Systems for Video Technology, Special Issue, vol. 15, no. 10, pp. 1234-1244.

Efficient on-line visualization of 3D textured models is essential for a variety of applications including not only games and e-commerce, but also heritage and medicine. To visualize 3D objects online, it is necessary to quickly adapt both mesh and texture to the available computational or network resources. Earlier research showed that after reaching a minimum required mesh density, high-resolution texture has more impact on human perception than a denser mesh. Given limited bandwidth, an important issue is how to extract features that best represent the original object, and how to allocate resources between mesh and texture data to achieve optimal perceptual quality. In this paper, we propose a textured mesh (TexMesh) model, which applies scale-space analysis (SSF) and perceptual evaluation to extract 3D features for textured mesh simplification and transmission. Texture data is divided into fragments to facilitate quality and bandwidth adaptation. Texture quality assignment is based on feature point distribution. On-line transmission is based on statistics gathered during preprocessing, which are stored in a priority queue and lookup tables. Quality of Service (QoS) requested by a client site can be met by applying an efficient adaptive algorithm to ensure optimal use of the specified time and available bandwidth, and at the same time preserving satisfactory quality. Our TexMesh framework integrates feature extraction, mesh simplification, texture reduction, bandwidth adaptation, and perceptual evaluation into a multi-scale visualization framework.

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