Interactive reconstruction via geometric probing
Article Abstract:
Geometric probing involves the determination of a geometric structure of some aspect of it from the results of a probe, or physical measuring device. Finger probes, or those that rely on tactile sensing such as used, for example, in robotics, is defined to be the first point of intersection p between a directed line l and an object P. Determination and verification are the fundamental problems in geometric probing. While determination counts the number of probes needed to reconstruct an object P, verification counts the number of probes needed to prove that P is the object in question. One question that must be answered in both cases is how much knowing the number of vertices of P helps in probing it. Finger probe models include hyperplane probes, silhouette probes, X-ray probes, half-space probes and cut-set probes.
Publication Name: Proceedings of the IEEE
Subject: Electronics
ISSN: 0018-9219
Year: 1992
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Geometric modeling and computer vision
Article Abstract:
Geometric matching algorithms enable computer vision systems to relate image data descriptions to geometric world model data in order to 'recognize' the image content. Specifically, received image signal data are mapped to a world model which includes data about world objects, data description entities, sensor data and their interrelations. Geometric models consist of polyhedra, quadrics, sweep representations, octrees and superellipsoids represented in parametric, implicit, digital, solution or graph forms. Boundary, boolean and sweep composition are often used to combine geometric primitives into complex entities. The matching problem between the computer-resident models and the acquired image may use point set, curve, surface and-or volume matching. Fractals and texture are also briefly discussed.
Publication Name: Proceedings of the IEEE
Subject: Electronics
ISSN: 0018-9219
Year: 1988
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On geometric sequence of reflection coefficients and Gaussian autocorrelations
Article Abstract:
A simpler method, than that of G Jacovitti and G Scarano, is developed to prove that a stationary random process with a Gaussian autocorrelation has a geometrically-decaying sequence of reflection coefficients. This lattice filtering problem is reinterpreted as an inverse scattering problem of determining the parameters of a discrete transmission line from its impulse reflection response. This can be easily solved using the Schur dynamic deconvolution algorithm.
Publication Name: Proceedings of the IEEE
Subject: Electronics
ISSN: 0018-9219
Year: 1988
User Contributions:
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