What are the state of the art methods for person segmentation and person pose identification
Check out Yang and Ramanan's work with flexible mixture of parts.  It starts with a central part, but pairs of parts that are attached are detected jointly by estimating the probability that the image area being queried supports the co-occurence of the attached parts in the image.  Error is presumed in the attachment and is minimized using a spring-like model.  Each part is detected using HOG-style techniques, and all pairs of parts in the human 'tree' are iterated over to determine the detection.  In my experience it has a very good false alarm rate, but requires hardware acceleration for real-time applications.