Editorial

Abstract

This issue contains four regular papers. The first paper, by Qingqiong Deng and Xiaopeng Zhang from the CAS Institute of Automation in China, Gang Yang from the Beijing Forestry University, and Marc Jaeger from the INRIA Saclay in Montpellier, France present a new foliage simplification framework for level of detail (LOD) of plant geometric models and forest rendering. Leaf density is introduced to adapt compression to the local distribution of leaves, so that more visually relevant details are kept. With a specific design of LOD storage structure, the costly hierarchical traversal of a binary tree is replaced by simple linear lookup array retrieval. This structure is GPU-oriented and decreases the communication between the CPU and the GPU for LOD level model loading in rendering. Sun-Uk Hwang, Beom-Chan Lee, Jeha Ryu, Kwan H. Lee, and Yong-Gu Lee from GIST-Mechatronics in Korea propose a temporal smoothing technique for haptic interaction using a sensing glove in multi-modal applications. The technique employs two processes: (1) a noise reduction method to reduce jitter noise at the sensors in the sensing glove, and (2) an adaptive force extrapolation for time-varying haptic and video frame rates. The authors have developed a test platform to assess a simple box model and relatively complex models such as gamephone, portable media player. The third paper, by Nicolas Stoiber from Orange Laboratory in France, Renaud Seguier from Supelec, and Gaspard Breton from Orange Laboratory present an animation system that gathers the advantages of two approaches in animation: parameter-based animation and performance-based animation. By analyzing a database of facial motion, the authors create the human appearance space, which provides a coherent and continuous parameterization of human facial movements, while encapsulating the coherence of real facial deformations. The method optimally constructs an analogous appearance face for a synthetic character. In the fourth paper, I-Chen Lin, Wen-Hsing Chang, Yung-Sheng Lo, Jen-Yu Peng, and Chan-Yu Lin also from the National Chiao Tung University in Taiwan introduce, in the last paper, a novel optimization framework for estimating the static or dynamic surfaces with details. The proposed method uses dense depths from a structured-light system or sparse ones from motion capture as the initial positions, and exploits non-Lambertian reflectance models to approximate surface reflectance. Multi-stage shape-from-shading is then applied to optimize both shape geometry and reflectance properties.