2003
DOI: 10.1109/tsmcb.2003.814299
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Moments of superellipsoids and their application to range image registration

Abstract: Abstract-Cartesian moments are frequently used global geometrical features in computer vision for object pose estimation and recognition. In the paper we derive a closed form expression for 3D Cartesian moment of order Ô ·Õ·Ö of a superellipsoid in its canonical coordinate system. We also show how 3D Cartesian moment of a globally deformed superellipsoid in general position and orientation can be computed as a linear combination of 3D Cartesian moments of the corresponding non-deformed superellipsoid in canoni… Show more

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Cited by 25 publications
(14 citation statements)
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“…We conduct discrete element method (DEM) simulations [16][17][18][19][20] of superellipsoid particles in a gravitydriven free-surface flow [12][13][14][21][22][23]. The particle shape is determined by the inside-outside function for superellipsoids [24][25][26]…”
mentioning
confidence: 99%
“…We conduct discrete element method (DEM) simulations [16][17][18][19][20] of superellipsoid particles in a gravitydriven free-surface flow [12][13][14][21][22][23]. The particle shape is determined by the inside-outside function for superellipsoids [24][25][26]…”
mentioning
confidence: 99%
“…However, there are some practical issues in PA. First, if the scan orientation of the source image is not identical to the orientation of the reference image (e.g., a sagittally scanned source image and an axially scanned reference image), the estimate obtained using PA will be incorrect [31] . To eliminate the constraint on scan orientation, higher moments can be introduced into the PA [41] , which would cause extra computational loads. Second, the PA requires whole brain information; if the brain is partially scanned, the estimate by PA could deviate.…”
Section: Discussionmentioning
confidence: 99%
“…Using that assumption, the configuration can be computed efficiently. Let the partÕs main axis be the axis of minimal inertia [2,22]. Our analysis of such objects showed that the main axes of scene parts are well aligned with true main axes of the object model parts.…”
Section: Interpretation Verificationmentioning
confidence: 90%