Animation of mesh models can be accomplished in many ways, including character animation with skinned skeletons, deformable models, or physic-based simulation. Generating animations with all of these techniques is time consuming and laborious for novice users; however adapting already available wide-range human motion capture data might simplify the process signi cantly. This thesis presents a method for retargeting human motion to arbitrary 3D mesh models with as little user interaction as possible. Traditional motion retargeting systems try to preserve original motion as is, while satisfying several motion constraints. In our approach, we use a few pose-to-pose examples provided by the user to extract desired semantics behind retargeting process by not limiting the transfer to be only literal. Hence, mesh models, which have di erent structures and/or motion semantics from humanoid skeleton, become possible targets. Also considering mesh models which are widely available and without any additional structure (e.g. skeleton), our method does not require such a structure by providing a build-in surface-based deformation system. Since deformation for animation purpose can require more than rigid behaviour, we augment existing rigid deformation approaches to provide volume preserving and cartoon-like deformation. For demonstrating results of our approach, we retarget several motion capture data to three well-known models, and also investigate how automatic retargeting methods developed considering humanoid models work on our models.