P. Hebert, D. Laurendeau, and D. Poussart, "Scene reconstruction and description: geometric primitive extraction from multiple view scattered data," in Proc. IEEE Conference on Computer Vision and Pattern Recognition, (New York), pp. 286--293, 1993.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....work Consolidation Recent technological and algorithmic advances have improved the process of automatic acquisition of 3D models. Acquiring the geometry of an object starts with data acquisition, usually performed with a range scanner. This raw data contains errors (e.g. line ofsight error [21, 47]) mainly due to noise intrinsic to the sensor used and its interaction with the real world object being acquired. For a non trivial object, it is necessary to perform multiple scans, each in its own coordinate system, and to register the scans [6] In general, areas of the objects are likely to be ....

P. Hebert, D. Laurendeau, and D. Poussart. Scene reconstruction and description: Geometric primitive extraction from multiple view scattered data. In IEEE Computer Vision and Pattern Recognition 1993.

....work Consolidation Recent technological and algorithmic advances have improved the process of automatic acquisition of 3D models. Acquiring the geometry of an object starts with data acquisition, usually performed with a range scanner. This raw data contains errors (e.g. line ofsight error [16, 37]) mainly due to noise intrinsic to the sensor used and its interaction with the real world object being acquired. For a non trivial object, it is necessary to perform multiple scans, each in its own coordinate system, and to register the scans [5] In general, areas of the objects are likely to be ....

P. Hebert, D. Laurendeau, and D. Poussart. Scene reconstruction and description: Geometric primitive extraction from multiple view scattered data. In IEEE Computer Vision and Pattern Recognition

....and shown to yield excellent results [11] 30] The remaining error lies in the scanner itself. For optical triangulation scanners, for example, this error has been shown to be ellipsoidal about the range points, with the major axis of the ellipse aligned with the lines of sight of the laser [13][24] Figure 4 illustrates the two dimensional case for a range curve derived from a single scan containing a row of range samples. In 3 (b) c) e) f) Isosurface Sensor n 2 n 1 D max D min (a) d) Sensor Figure 4. Combination of signed distance and weight functions in two ....

P. Hebert, D. Laurendeau, and D. Poussart. Scene reconstruction and description: geometric primitive extraction from multiple viewed scattered data. In Proceedings (a) (b) (e) (f) (g) (c) (d)

....section. Thus, there are different uncertainties along different surface orientations and they need to be handled appropriately. Further, the measurement error is not uniformly distributed over the entire image. The error may depend on the position of a point, relative to the object surface. In [7] a measurement error model dealing with the sensor s viewpoint has been proposed for surface reconstruction, to recover straight line segments from noisy single scan 3D surface profiles. In this report we investigate the effect of measurement noise on the registration of multiple views. Our ....

P. Hebert, D. Laurendeau, and D. Pousart, "Scene reconstruction and description: Geometric primitive extraction from multiple view scattered data," in IEEE Conference on Computer Vision and Pattern Recognition, pp. 286--292, New York City, NY 1993.

....and shown to yield excellent results [11] 30] The remaining error lies in the scanner itself. For optical triangulation scanners, for example, this error has been shown to be ellipsoidal about the range points, with the major axis of the ellipse aligned with the lines of sight of the laser [13][24] Figure 4 illustrates the two dimensional case for a range curve derived from a single scan containing a row of range samples. In practice, we use a fixed point representation for the signed distance func3 (b) c) e) f) Isosurface Sensor n 2 n 1 D max D min (a) d) Sensor Figure 4. ....

P. Hebert, D. Laurendeau, and D. Poussart. Scene reconstruction and description: geometric primitive extraction frommultiple viewed scattered data. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pages 286--292, June 1993.

....appropriately during view registration. Furthermore, the measurement error is not uniformly distributed over the entire image. The error may depend on the position of a point, relative to the object surface. A measurement error model dealing with the sensor s viewpoint has been previously proposed [11] for surface reconstruction where the emphasis was to recover straight line segments from noisy single scan 3D surface profiles. In this paper, we show that the noise in z values affects the estimation of the tangential plane parameters differently depending on how the surface is oriented. Since ....

P. Hebert, D. Laurendeau, and D. Pousart, "Scene reconstruction and description: Geometric primitive extraction from multiple view scattered data," in Proc. IEEE Conference on Computer Vision and Pattern Recognition, (New York City, NY), pp. 286--292, 1993.

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P. Hebert, D. Laurendeau, and D. Poussart, "Scene reconstruction and description: geometric primitive extraction from multiple view scattered data," in Proc. IEEE Conference on Computer Vision and Pattern Recognition, (New York), pp. 286--293, 1993.

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