The authors present 3D-POLY, a working system for recognizing objects in the presence of occlusion and against cluttered backgrounds The time complexity of this system is only O(n/sup 2/) for single-object recognition, where n is the number of features on the project The organisation of the feature data for the models is based on a data structure called the feature sphere Efficient constant-time algorithms for assigning a feature to its proper place on a feature sphere and for extracting the neighbors of a given feature from the feature sphere representation are presented For hypothesis generation, local feature sets are used The combination of the feature sphere idea for streamlining verification and the local feature sets for hypothesis generation results in a system whose time complexity has a low-order polynomial bound >

/pdf/a-robot-vision-system-for-recognizing-3d-objects-in-low-2yaaik6hly.pdf

A robot vision system for recognizing 3D objects in low-order polynomial time

Due to the recent improvements in laser scanning technology, 3D visualization and modeling, there is an increasing need for tools supporting the automatic search for 3D objects in archives. In this paper we describe a new geometric approach to 3D shape comparison and retrieval for arbitrary objects described by 3D polyhedral models that may contain gaps. In contrast with the existing approaches, our approach takes the overall relative spatial location into account by representing the 3D shape as a weighted point set. To compare two objects geometrically, we enclose each object by a 3D grid and generate a weighted point set, which represents a salient point for each non-empty grid cell. We compare three methods to obtain a salient point and a weight in each grid cell: (1) choosing the vertex in the cell with the highest Gaussian curvature, and choosing a measure as weight for that curvature, (2) choosing the area-weighted mean of the vertices in the cell, and choosing a measure as weight denoting the normal variation of the facets in the cell and (3) choosing the center of mass of all vertices in the cell, and choosing one as weight. Finally, we compute the similarity between two shapes by comparing their weighted point sets using a new shape similarity measure based on weight transportation that is a variation of the Earth Mover's Distance. Unlike the Earth Mover's Distance, the new shape similarity measure satisfies the triangle inequality. This property makes it suitable for use in indexing schemes, that depend on the triangle inequality, such as the one we introduce, based on the so-called vantage objects. The strength of our approach is proven through experimental results using a database consisting of 133 models such as mugs, cars and boats, and a database consisting of 512 models, mostly air planes, classified into conventional air planes, delta-jets, multi-fuselages, biplanes, helicopters and other models. The results show that the retrieval performance is better than related shape matching methods.

/pdf/polyhedral-model-retrieval-using-weighted-point-sets-38wt8klslj.pdf

Polyhedral model retrieval using weighted point sets

Gamma-ray spectroscopy was revolutionized with the introduction of high energy-resolution semiconductor germanium (Ge) detectors in the early 1960s. This led to the large increase in sensitivity realized by today’s arrays of Compton-suppressed Ge detectors. A still larger increase in sensitivity is expected by implementing the new concept of tracking. A tracking array consists of highly segmented Ge detectors (that can cover the full 4π solid-angle) in which γ rays will be identified by measuring and tracking every γ -ray interaction. This article reviews the physics motivation for such detectors and the development of the new technologies involved. The concept of tracking is explained using the example of a proposed array called γ -ray energy tracking array (GRETA).

/pdf/developments-in-large-gamma-ray-detector-arrays-1zaozopr2a.pdf

Developments in large gamma-ray detector arrays

This paper presents a new approach to the structure of amorphous semiconductors. Regular structures (‘polytopes') defined in three-dimensional curved space are used to describe an ideal order. We assume that disorder in real material is comparable to the disorder induced by the mapping of the polytope onto Euclidian space. This mapping has two effects: elastic distortions and internal cut surfaces. These surfaces can be relaxed by disclination lines. A systematic generation of amorphous Si: H structural models can be achieved by the saturation, with hydrogen atoms, of the dangling bonds arising near the defects.

Order and disorder in amorphous, tetrahedrally coordinated semiconductors A curved-space description

Most databases for spherically distributed data are not structured in a manner consistent with their geometry. As a result, such databases possess undesirable artifacts, including the introduction of "tears" in the data when they are mapped onto a flat file system. Furthermore, it is difficult to make queries about the topological relationship among the data components without performing real arithmetic. The sphere quadtree (SQT), which is based on the recursive subdivision of spherical triangles obtained by projecting the faces of an icosahedron onto a sphere, eliminates some of these problems. The SQT allows the representation of data at multiple levels and arbitrary resolution. Efficient search strategies can be implemented for the selection of data to be rendered or analyzed by a specific technique. Furthermore, sphere quadtrees offer significant potential for improving the accuracy and efficiency of spherical surface rendering algorithms as well as for spatial data management and geographic information systems. Most importantly, geometric and topological consistency with the data is maintained.

Rendering and managing spherical data with sphere quadtrees

Polyhedra : A Visual Approach

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Polyhedra : A Visual Approach