<H1>1. Introduction</H1>
      
      Several recent major movie releases have demonstrated that the motion of clothing adds greatly to the appearance of a virtual character. This effect is particularly compelling for scenes that include both real and synthetic actors such as those with Yoda and Anakin Skywalker in Episode II: Attack of the Clones. In such scenes, the virtual clothing must move and be rendered so that it blends in seamlessly with the motion and appearance of the real clothing in the scene. Realistic virtual clothing is possible now because of recent advances in cloth simulation techniques 
4 , 9 , 5 , 37 , 6 . The motion of fabric is determined by resistance to bending, stretching, shearing, external forces, aerodynamic effects, friction, and collisions. Although with the right set of parameters good simulators produce very realistic looking motion, choosing parameters that will provide a particular appearance remains a time consuming task that requires the computation and viewing of many forward simulations. Some parameters can be chosen based on the animator’s intuition about the fabric—a knit fabric is more stretchy than a woven fabric such as linen, for example. But not all the parameters of a cloth simulator are intuitive or map directly to measurements that can made by a system such as the Kawabata system 
22 . In our paper, we address this problem by using optimization to automatically determine these parameters from a sequence of video frames of the fabrics under consideration. The parameters are optimized on a set of static shots and motion clips of a small swatch of a particular fabric and then tested on a simulation of a full skirt made from that fabric. We designed the swatch tests to span the space of behaviors that we expect to see in the final sequences of motion with the skirt so that all parameters can be tuned appropriately. We use simulated annealing for the optimization step with an optimization function that assesses the extent to which the folds in the simulated and physical fabric match. This match is evaluated by means of a shape metric that uses projected light to detect surface orientation in real and simulated fabrics. The metric is tuned to be most sensitive along folds and to discount planar regions. We use the system to find the parameters for four different fabrics. We show the match between the video footage and the simulated motion on the calibration experiments, on new video sequences for the swatches, and on a simulation of a full skirt as shown in the image on the previous page.
      c The Eurographics Association 2003.
      Bhat et al. / Estimating Cloth Simulation Parameters from Video
      
        