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The recognition of shapes in images using Pairwise Geometric His-tograms has previously been confined to fixed scale shape. Although the geometric representation used in this algorithm is not scale invariant , the stable behaviour of the similarity metric as shapes are scaled enables the method to be extended to the recognition of shapes over a range of(More)
This paper deals with the constrained shape reconstruction of objects having quadric patches. The incorporation of geometric constraints in object reconstruction was used rst by Porrill 10]. His approach combined the Kalman lter equations with linearized constraint equations. This technique was improved by De Geeter et al 5] to reduce the eeects of(More)
The paper proposes a reliable method for estimating quadric surfaces from 3D range data in the framework of object recognition and localization or reverse engineering. Instead of estimating a quadric surface in isolation, the approach ts all the surfaces captured in the scene together taking into account the geometric relationships between them and their(More)
This paper deals with the constrained reconstruction of 3D geometric models of objects from range data. It describes a new technique of global shape improvement based upon feature positions and geometric constraints. It suggests a general incre-mental framework whereby constraints can be added and integrated in the model reconstruction process, resulting in(More)
Pairwise geometric histograms have been demonstrated as an eeective descriptor of arbitrary 2-dimensional shape which enable robust and eecient object recognition in complex scenes. In this paper we describe how the approach can be extended to allow the representation and classiication of arbitrary 2 1 2-and 3-dimensional surface shape. This novel(More)
Pairwise geometric histograms have been demonstrated as an eeective descriptor of arbitrary 2-dimensional shape which enable robust and eecient object recognition in complex scenes. In this paper we describe how the approach can be extended to allow the representation and classiication of arbitrary 2 1 2-and 3-dimensional surface shape. This novel(More)
In this paper we show how the cost of a structured light, range nding system can be substantially reduced by visually tracking the structured light source. To be able to recover range measurements using a structured light range nder the relative positions of the struc-tured light source and light sensor must be known. This is typically achieved by carefully(More)
In this work we have addressed the question of whether it is possible to extract parametric models of features from poor quality 3D data. In doing so we have examined the applicability of an evolutionary strategy to the problem of tting constrained parametric models. In the rst phase, a background surface is tted and removed leaving points of discontinuity(More)
While the problem of model tting for 3-dimensional range data has been addressed with some success, the problem of increasing the accuracy of the whole t still remains. This paper describes a technique of global shape improvement based upon feature position and shape constraints. These constraints may be globally applied or inferred from general engineering(More)
This paper examines the application of an evolutionary algorithm (GENO-COP III) to the problem of tting surfaces and lines to both 2D synthetic and real 3D range data. The tting is performed with both non-linear (domain) constraints and with non-linear (geometric and relational) constraints. Example ttings are given as well as an explanation of experimantal(More)