This paper presents a Time-of-Flight (ToF) camera based system for hand motion and gesture tracking. A 27 degree of freedom (DOF) hand model is constructed and fleshed out by ellipsoids. This allows the synthesis of range images of the model through projective geometry. The hand pose is then tracked with a particle filter by statistically measuring the hypothetical pose against the ToF input image; where the inside/outside alignment of the hand pixels and the depth differences serve as classifying metrics. The high DOF tracking problem for the particle filter is addressed by reducing the high dimensionality of the joint angle space to a low dimensional space via Principal Component Analysis (PCA). The basis vectors are learned from a few basic model configurations and the transformations between these poses. This results in a system capable of practical hand tracking in a restricted gesture configuration space.