Abstract: Given a motion capture sequence with occlusions, how can we recover the missing values, respecting bone-length constraints? Recent past work uses Linear Dynamical Systems (LDS), which work well, except for occasionally violating such constraints, and thus lead to unrealistic results. Our main contribution is a principled approach for preserving such distances. Specifically (a) we show how to formulate the problem as a constrained optimization problem, using two variations: hard constraints, and soft constraints; (b) we show how to efficiently solve both variations; (c) we demonstrate the realism of our approaches against competitors, on real motion capture data, illustrating that our 'soft constraints' version eventually produces more realistic results.