caa a22 4500 469036052 CHVBK 20180323132756.0 cr unu---uuuuu 170328e19921101xx s 000 0 eng 10.1007/BF00129682 doi (NATIONALLICENCE)springer-10.1007/BF00129682 Surface shape from the deformation of apparent contours [Elektronische Daten] [Roberto Cipolla, Andrew Blake] The spatiotemporal analysis of deforming silhouettes (apparent contours) is here extended using the mathematics of perspective projections and tools from differential geometry. Analysis of the image motion of a silhouette or apparent contour enables computation of local surface curvature along the corresponding contour generator on the surface, assuming viewer motion is known. To perform the analysis, a spatiotemporal parameterization of image-curve motion is needed, but is underconstrained (a manifestation of the well-known aperture problem). It is shown that an epipolar parameterization is most naturally matched to the recovery of surface curvature. One immediate facility afforded by the analysis is that surface patches can be reconstructed in the vicinity of contour generators. Once surface curvature is known, it is possible to discriminate extremal contours from other fixed curves in space. Furthermore, the known robustness of parallax as a cue to depth extends to the case of surface curvature. Its derivative—rate of parallax—is shown theoretically to be a curvature cue that is robust to uncertainties in the known viewer motion. This robustness has been confirmed in experiments. Finally, the power of the new analysis for robotics applications is demonstrated. Illustrations are given of an Adept robot, equipped with a CCD camera, circumnavigating curved obstacles. When further equipped with a suction gripper the robot manipulator can pick up an object by its curved surface, under visual guidance. Kluwer Academic Publishers, 1992 Cipolla Roberto Department of Engineering, University of Cambridge, CB2 1PZ, Cambridge, England aut Blake Andrew Department of Engineering Science, University of Oxford, OX1 3PJ, Oxford, England aut International Journal of Computer Vision Kluwer Academic Publishers 9/2(1992-11-01), 83-112 0920-5691 9:2<83 1992 9 11263 https://doi.org/10.1007/BF00129682 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF00129682 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Cipolla Roberto Department of Engineering, University of Cambridge, CB2 1PZ, Cambridge, England aut NATIONALLICENCE 700 1- Blake Andrew Department of Engineering Science, University of Oxford, OX1 3PJ, Oxford, England aut NATIONALLICENCE 773 0- International Journal of Computer Vision Kluwer Academic Publishers 9/2(1992-11-01), 83-112 0920-5691 9:2<83 1992 9 11263 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer