Part-based initialization for hand tracking
Initializing hand/finger articulation for tracking is a very challenging problem, mainly because hand articulation is complicated and it has a large number of degrees of freedom. Most existing algorithms initialize tracking manually, or use a nearest-neighbor search with restricting the number of possible hand gestures. This paper presents a new solution to this problem by increasing the dimensionality but taking advantage of the sparseness. The basic idea is to divide the set of phalange joint angles into many overlapping subsets. As each subset has a much smaller number of joint angles, it is much easier to design a smaller-scale articulation estimator. The estimation of the whole hand is done by the collaboration of a network of dependent smaller-scale estimators. This paper describes a novel way of designing the smaller-scale estimators as well as a principled way of fusing the estimates. A tracking system is also shown by using this initialization technique.