1. A computerized method for creating a classifier, comprising the steps of: receiving, by a computer, a training sample set and a candidate part-based action set; creating, by the computer, one or more weak classifier sets based on the training sample set and the candidate part-based action set wherein the weak classifier sets have assigned error rates based on a comparison of the training sample set and the candidate part-based action set; and creating, by the computer, a strong classifier based on the one or more weak classifier sets by combining a first weak classifier with a lowest assigned error rate from a selected first weak classifier set with a second weak classifier with a lowest assigned error rate from a selected second weak classifier set.