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 target bounding box in a first video frame; segmenting the target image into a plurality of parts each contained in a separate part bounding box; training a detector for each of the plurality of parts in the first video frame; in a next video frame, sampling the position of a target bounding box in a particle filter framework; for each of the plurality of parts, generating a confidence map from a search region for a possible location of the part by applying a plurality of sliding windows of polygonally arranged pixels, each sliding window centered around a pixel in the search region for the part 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.