Pose recognition in indoor environments using a fisheye camera and a parametric human model

In this paper we present a system that uses computer vision techniques and a deformable 3D human model, in order to recognize the posture of a monitored person, given the segmented human silhouette from the background. The video data are acquired indoors from a fixed fish-eye camera placed in the living environment. The implemented 3D human model collaborates with a fish-eye camera model, allowing the calculation of the real human position in the 3D-space and consequently recognizing the posture of the monitored person. The paper discusses the details of the human model and fish-eye camera model, as well as the posture recognition methodology. Initial results are also presented for a small number of video sequences, of walking or standing humans.