Human motion detection using Markov random fields
In this paper, we propose Markov random fields (MRFs) to automatically detect a moving human body through minimizing the joint energy of the MRF for the velocity and relative position of body parts. The relaxation labeling algorithm is employed to find the best body part labeling configuration between MRFs and observed data. We detect a walking motion viewed monocularly based on point features, where some points are from the unoccluded body parts and some belong to the background. The results show that MRFs can detect human motions robustly and accurately.
human motion markov random fields relaxation labeling