Accurate Visual Metrology from Single and Multiple Uncalibrated Images [Winner of The British Computer Society Distinguished Dissertation Award 2000] - Criminisi, Antonio (Springer-Verlag, 2001)
This monograph presents some research carried out by the author into three- dimensional visual reconstruction during his studies for the achievement of a Doctor of Philosophy Degree at the University of Oxford. This book constitutes the author’s D.Phil. dissertation which, having been awarded the British Computer Society Distinguished Dissertation Award for the year 2000, has kindly been published by Springer-Verlag London Ltd. The work described in this book develops the theory of computing world measurements (e.g. distances, areas etc.) from photographs of scenes and reconstructing three-dimensional models of the scene. The main tool used is projective geometry which forms the basis for accurate estimation algorithms. Novel methods are described for computing virtual reality-like environments from any kind of perspective image. The techniques presented employ uncalibrated images; no knowledge of the internal parameters of the camera (such as focal length and aspect ratio) nor its pose (position and orientation with respect to the viewed scene) are required at any time. Extensive use is made of geometric characteristics of the scene. Thus there is no need for specialized calibration devices. A hierarchy of novel, accurate and flexible techniques is developed to address a number of different situations ranging from the absence of scene metric information to cases where some world distances are known but there is not sufficient information for a complete camera calibration. The geometry of single views is explored and monocular vision shown to be sufficient to obtain a partial or complete three-dimensional reconstruction of a scene. To achieve this, the properties of planar homographies and planar homologies are extensively exploited. The geometry of multiple views is also investigated, particularly the use of a parallax-based approach for structure and camera recovery. The duality between two-view and three-view configurations is described in detail. In order to pro