This paper addresses the problem of acquiring realistic visual models of the shape and appearance of complex three-dimensional (3D) scenes from collec-tions of images, a process dubbed 3D photography. We focus on three instances of this problem: (1) the image-based construction of projective visual hulls of complex surfaces from weakly-calibrated photographs; (2) the automated matching and registration of photographs of textured surfaces using affine-invariant patches and their geometric relationships; and (3) an approach to projective motion analysis and self-calibration explicitly accounting for natural camera constraints such as zero skew and capable of handling large numbers of images in an efficient and uniform manner. We also briefly discuss some relat-ed applications of oriented differential projective geometry to computer vision problems, including the determination of the ordering of rim segments in pro-jective visual hull computation, and a purely projective proof of Koenderink's famous characterization of the local shape of visual contours.