Video-games and animated movies require a sophisticated multistage set of processes known as the animation pipeline for collecting animation data, beginning with actors in a Motion Capture Studio and ending in animated digital characters. Throughout the animation pipeline, varying levels of manual human intervention are typically needed to ensure animation quality. Passive markers used for Motion Capture require manual cleanup by trained MOCAP artists to fix issues such as marker occlusions, marker swaps, and noise. This thesis proposes a novel method to automate this process that works by identifying broken marker path segments and subsequently reconstructing broken markers using a kinematic reference. The result is a state-of-the-art method that outperforms existing solutions by being simultaneously more accurate as well as easier to integrate into existing animation pipelines. Once marker data is cleaned, studios will often want to retarget the captured data onto different characters, a step that usually requires the manual tweaking of various retargeting parameters in proprietary software. This thesis proposes a batch mesh-based retargeting algorithm that uses Jacobian Inverse Kinematics tracking mesh vertices to retarget animations between different skeletal rigs. This results in an efficient algorithm that is capable of retargeting multiple animation clips without requiring the manual tweaking of parameters specified.