Pose recognition using the Radon transform

Human pose recognition is an active topic of vision research that has applications in diverse fields such as collaborative virtual environments and robot teleoperation. We propose a novel method for the recognition of human pose using the Radon transform. A binary skeleton representation of the human subject is computed and information concerning the pose is extracted from the parametric Radon transform. The Radon transform generates maxima corresponding to specific orientations of the skeletal representation. A spatial maxima mapping technique is developed to recognize pose from the Radon transform maxima. This technique has the potential to provide information about the exact orientation of pose segments. Experiments with real image data highlight the advantages of this approach.