Efficient view point selection for silhouettes of convex polyhedra

AbstractSilhouettes of polyhedra are an important primitive in application areas such as machine vision and computer graphics. In this paper, we study how to select view points of convex polyhedra such that the silhouette satisfies certain properties. Specifically, we give algorithms to find all projections of a convex polyhedron such that a given set of edges, faces and/or vertices appear on the silhouette.We present an algorithm to solve this problem in O(k2) time for k edges. For orthogonal projections, we give an improved algorithm that is fully adaptive in the number l of connected components formed by the edges, and has a time complexity of O(klogk+kl). We then generalize this algorithm to edges and/or faces appearing on the silhouette

Interleaving 3D Model Feature Prediction and Matching to Support Multi-Sensor Object Recognition

Recognizing 3D modeled objects through alignment of object and sensor features requires a means of predicting matchable features. This paper presents a system which performs online feature prediction for CAD modeled objects and tightly couples prediction with matching. For the ATR domain, detailed CAD models of objects are available in this application, as is both range and optical imagery. Matching begins with an initial hypothesis which is refined through an iterative generate-and-test procedure. Matching interleaves feature prediction and adjustment of model-to-sensor geometry until a locally optimal match is obtained. In addition, sensor-to-sensor geometry is also adjusted, allowing the algorithm to correct minor mis-registrations between range and optical imagery. While the resulting match is locally optimal in terms of the complete space of possible matches, it globally preserves the 3D constraints implied by sensor and object geometry. Results on real data are presented which de..