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Iterative point matching for registration of freeform curves and surfaces
, 1994
"... A heuristic method has been developed for registering two sets of 3D curves obtained by using an edgebased stereo system, or two dense 3D maps obtained by using a correlationbased stereo system. Geometric matching in general is a difficult unsolved problem in computer vision. Fortunately, in ma ..."
Abstract

Cited by 519 (6 self)
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A heuristic method has been developed for registering two sets of 3D curves obtained by using an edgebased stereo system, or two dense 3D maps obtained by using a correlationbased stereo system. Geometric matching in general is a difficult unsolved problem in computer vision. Fortunately, in many practical applications, some a priori knowledge exists which considerably simplifies the problem. In visual navigation, for example, the motion between successive positions is usually approximately known. From this initial estimate, our algorithm computes observer motion with very good precision, which is required for environment modeling (e.g., building a Digital Elevation Map). Objects are represented by a set of 3D points, which are considered as the samples of a surface. No constraint is imposed on the form of the objects. The proposed algorithm is based on iteratively matching points in one set to the closest points in the other. A statistical method based on the distance distribution is used to deal with outliers, occlusion, appearance and disappearance, which allows us to do subsetsubset matching. A leastsquares technique is used to estimate 3D motion from the point correspondences, which reduces the average distance between points in the two sets. Both synthetic and real data have been used to test the algorithm, and the results show that it is efficient and robust, and yields an accurate motion estimate.
On local matching of freeform curves
 In Proc. BMVC
, 1992
"... Geometric matching in general is a difficult unsolved problem in computer vision. Fortunately, in many practical applications, some a priori knowledge exists which considerably simplifies the problem. In visual navigation, for example, the motion between successive positions is usually either small ..."
Abstract

Cited by 10 (0 self)
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Geometric matching in general is a difficult unsolved problem in computer vision. Fortunately, in many practical applications, some a priori knowledge exists which considerably simplifies the problem. In visual navigation, for example, the motion between successive positions is usually either small or approximately known, but a more precise registration is required for environment modeling. The algorithm described in this paper meets this need. Objects are represented by freeform curves, i.e., arbitrary space curves of the type found in practice. A curve is available in the form of a set of chained points. The proposed algorithm is based on iteratively matching points on one curve to the closest points on the other. A leastsquares technique is used to estimate 3D motion from the point correspondences, which reduces the average distance between curves in the two sets. Both synthetic and real data have been used to test the algorithm, and the results show that it is efficient and robust, and yields an accurate motion estimate.
Orienting Toleranced . . .
, 2000
"... Parts manufactured to tolerances have variations in shape. Most previous work in robotic manipulation assumes that parts do not have shape variations. Orienting devices such as bowl feeders often fail due to variations in part shape. We study the effects of uncertainty in part shape on orienting to ..."
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Parts manufactured to tolerances have variations in shape. Most previous work in robotic manipulation assumes that parts do not have shape variations. Orienting devices such as bowl feeders often fail due to variations in part shape. We study the effects of uncertainty in part shape on orienting to develop systems that can orient toleranced polygonal parts. We present a tolerance model in which the part center of mass and vertices lie in circular uncertainty zones around their nominal positions. The variations in part shape are characterized by the tolerance model and the part's nominal shape. We describe the nondeterminism that arises due to part shape uncertainty for a conveyorbased orienting system and show that sensorbased and sensorless orienting plans can exist for toleranced polygonal parts. We present implemented planners that generate orienting plans for the entire variational class of part shapes given a nominal part shape and tolerance bounds. These plans use both deterministic and nondeterministic actions to orient the parts, and we describe experiments to demonstrate them.
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Additional services and information for Medical Decision Making can be found at: