Abstract: We present a method for automatically generating reduced marker layouts for marker-based optical motion capture of human hand motions. Reducing the number of markers on the hand is important to ensure the generated motions are performed in a natural way and indeed a reduced marker set might be a technical requirement should simultaneous body motion capture also have to be carried out. The employed motion reconstruction method is based on subspace-constrained inverse kinematics, which allows for the recovery of realistic hand movements even from sparse input data. Our marker layout optimization is sensitive to the kinematic structure and the subspace representations of hand articulations utilized in the reconstruction method in order to generate sparse marker configurations that are optimal for solving the constrained inverse kinematics problem. We propose specific quality criteria for reduced marker sets that combine numerical stability with geometric feasibility of the resulting layout. These criteria are combined in an objective function that is minimized using a specialized surface-constrained particle swarm optimization scheme. Our method provides a principled way for determining reduced marker layouts based on subspace representations of hand articulations.