Issue No. 04 - April (2009 vol. 31)
Erik Murphy-Chutorian , Google Inc., Mountain View
Mohan Manubhai Trivedi , University of California, San Diego, La Jolla
The capacity to estimate the head pose of another person is a common human ability that presents a unique challenge for computer vision systems. Compared to face detection and recognition, which have been the primary foci of face-related vision research, identity-invariant head pose estimation has fewer rigorously evaluated systems or generic solutions. In this paper, we discuss the inherent difficulties in head pose estimation and present an organized survey describing the evolution of the field. Our discussion focuses on the advantages and disadvantages of each approach and spans 90 of the most innovative and characteristic papers that have been published on this topic. We compare these systems by focusing on their ability to estimate coarse and fine head pose, highlighting approaches that are well suited for unconstrained environments.
Introductory and Survey, Computer vision, Modeling and recovery of physical attributes, Human-centered computing, Vision I/O, Face and gesture recognition, Evaluation/methodology
E. Murphy-Chutorian and M. M. Trivedi, "Head Pose Estimation in Computer Vision: A Survey," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 31, no. , pp. 607-626, 2008.