caa a22 4500 469036125 CHVBK 20180323132756.0 cr unu---uuuuu 170328e19920701xx s 000 0 eng 10.1007/BF00126399 doi (NATIONALLICENCE)springer-10.1007/BF00126399 Measurement and integration of 3-D structures by tracking edge lines [Elektronische Daten] [James Crowley, Patrick Stelmaszyk, Thomas Skordas, Pierre Puget] This article describes techniques for dynamically modeling the 2-D appearance and 3-D geometry of a scene by integrating information from a moving camera. These techniques are illustrated by the design of a system that constructs a geometric description of a scene from the motion of a camera mounted on a robot arm. A framework for dynamic world modeling is described. The framwork presents the fusion of perceptual information as a cyclic process composed of three phases: Predict, Match, and Update. A set of mathematical tools are presented for each of these phases. The use of these tools is illustrated by the design of a system for tracking edge lines in image coordinates and inferring the 3-D position from a known camera motion. The movement of edge-lines in a sequence of images is measured by tracking to maintain an image-plane description of movement. This description is composed of a list of edge-segments represented as a parametric primitive. Each parameter is composed of an estimated value, a temporal derivative, and a covariance matrix. Line-segment parameters are updated using a Kalman filter. The correspondence between observed and predicted segments is determined by a nearest-neighbor matching algorithm using distance between parameters normalized by covariance. It is observed that constraining the acceleration of edge-lines between frames permits the use of a very simple matching algorihtm, thus yielding a very short cycle time. Three-dimensional structure is computed using the correspondence provided by the 2-D segment tracking process. Fusion of 3-D data from different view points provides an accurate representation of the geometry of objects in the scene. An extended Kalman filter is applied to the inference of the 3-D position and orientation parameters of 2-D segments. This process demonstrates that 2-D tracking provides the information for an inexpensive technique for estimating 3-D shape from motion. Results from several image sequences taken from a camera mounted on a robot arm are presented to illustrate the reliability and precision of the technique. Kluwer Academic Publishers, 1992 Crowley James LIFIA (IMAG), I.N.P. Grenoble, 46 Ave Félix Viallet, 38031, Grenoble, France aut Stelmaszyk Patrick I.T.M.I., Ave des Pérs, 38240, Meylan, France aut Skordas Thomas I.T.M.I., Ave des Pérs, 38240, Meylan, France aut Puget Pierre I.T.M.I., Ave des Pérs, 38240, Meylan, France aut International Journal of Computer Vision Kluwer Academic Publishers 8/1(1992-07-01), 29-52 0920-5691 8:1<29 1992 8 11263 https://doi.org/10.1007/BF00126399 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF00126399 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Crowley James LIFIA (IMAG), I.N.P. Grenoble, 46 Ave Félix Viallet, 38031, Grenoble, France aut NATIONALLICENCE 700 1- Stelmaszyk Patrick I.T.M.I., Ave des Pérs, 38240, Meylan, France aut NATIONALLICENCE 700 1- Skordas Thomas I.T.M.I., Ave des Pérs, 38240, Meylan, France aut NATIONALLICENCE 700 1- Puget Pierre I.T.M.I., Ave des Pérs, 38240, Meylan, France aut NATIONALLICENCE 773 0- International Journal of Computer Vision Kluwer Academic Publishers 8/1(1992-07-01), 29-52 0920-5691 8:1<29 1992 8 11263 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer