1. A method for detecting and tracking objects comprising: receiving a video sequence including a plurality of sequential video frames from a video camera; selecting a target image in a first video frame; segmenting the target image into at least one identifiable part in a part bounding box; training a detector for each of the at least one part in the first video frame; in a next video frame, sampling the position of a part bounding box in a particle filter framework; for each at least one part, generating a confidence map from a search region for the possible location of the at least one part by applying a plurality of sliding windows of polygonally arranged pixels, each sliding window centered around each pixel in the search region for the at least one part located in the first video frame; and generating a tracking score for each sliding window corresponding to a probability of the part being centered in each sliding window in the next video frame.