Murphy-Chutorian Erik, Trivedi Mohan Manubhai
Google Inc., Mountain View, CA 94043, USA.
IEEE Trans Pattern Anal Mach Intell. 2009 Apr;31(4):607-26. doi: 10.1109/TPAMI.2008.106.
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.
估计他人头部姿势的能力是人类的一种常见能力,这对计算机视觉系统提出了独特的挑战。与作为面部相关视觉研究主要焦点的面部检测和识别相比,身份不变的头部姿势估计的严格评估系统或通用解决方案较少。在本文中,我们讨论了头部姿势估计中固有的困难,并进行了一次有条理的综述,描述了该领域的发展历程。我们的讨论重点在于每种方法的优缺点,涵盖了关于该主题已发表的90篇最具创新性和特色的论文。我们通过关注这些系统估计粗略和精细头部姿势的能力来对它们进行比较,突出那些非常适合无约束环境的方法。