The development of methods and tools for the generation of visually appealing motion sequences using prerecorded motion capture data has become an important research area in computer animation. In particular, data-driven approaches have been used for reconstructing high-dimensional motion sequences from low-dimensional control signals. In this article, we contribute to this strand of research by introducing a novel framework for generating full-body animations controlled by only four 3D accelerometers that are attached to the extremities of a human actor. Our approach relies on a knowledge base that consists of a large number of motion clips obtained from marker-based motion capturing. Based on the sparse accelerometer input a cross-domain retrieval procedure is applied to build up a lazy neighborhood graph in an online fashion. This graph structure points to suitable motion fragments in the knowledge base, which are then used in the reconstruction step. Supported by a kd-tree index structure, our procedure scales to even large datasets consisting of millions of frames. Our combined approach allows for reconstructing visually plausible continuous motion streams, even J. Tautges and T. Helten were financially supported by grants from Deutsche Forschungsgemeinschaft (WE 1945/5-1 and MU 2686/3-1).

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In this paper we will present a system to use three dimensional computer graphics in garment design. This system is capable to visualize the "real", i.e. the physically correct, appearance of a knitted fabric. A fast visualization of a physically correct micro-structure garment is of crucial importance in textile industry, since it enables fast and less expensive product development. This system may be either used in the design of new products or teaching the art of knitted fabrics. We use in our system directly the produced machine-code of the design system for knitting machines. A physical model, a particle system, is used to calculate the dynamics of the micro-structure of the knitted garment.