We present an interactive character posing scheme based on a learned prior model from large motion database. The proposed scheme aims at generating poses that look as natural as possible while satisfying user constraints. We use an adaptive cluster algorithm to select a representative frame-set from the database, and a sparse approximation algorithm to accelerate the training and posing processes.