A motion‐field‐based data‐driven method for hair animation. (21st May 2018) - Bao, Yongtang; Qi, Yue
Abstract: We propose a motion‐field‐based data‐driven approach that animates static hair models from a set of precomputed motion data. We first sample a motion sequence to construct a motion database from physics‐based hair simulation data or dynamic hair capture data. We also define the preliminary definitions of motion states and construct a motion field for this motion database. Finally, we generate a sequence of target hairstyle from the input motion field by strand correspondence and motion control. Experimental results show that our approach achieves comparable quality with physics‐based methods but in orders of magnitude faster performance. Abstract : A data‐driven approach is used to animate static hairstyles from a set of precomputed motion data.