Lower limb pose estimation for monitoring the kicking patterns of infants

Abstract

Monitoring the spontaneous kicking patterns of infants can give insight into their development. A computer vision based method for estimating the pose of an infant's leg from range images is presented in this paper. After some manual inputs for initialization, the range data associated with the infant is extracted. The method uses Robust Point Set Registration (RPSR) to fit an articulated model to the subject in every frame in the sequence, thus it provides the joint trajectories over time of the kicking kinematics. For validation, the method is used to track the articulation of a robotic humanoid that was programmed to kick in a fashion similar to an infant. Furthermore, the method is applied to a sequence collected from an actual infant and the resultant signal estimates are presented.