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Bounding overwatch
About: Bounding overwatch is a research topic. Over the lifetime, 966 publications have been published within this topic receiving 15156 citations.
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TL;DR: It is shown in the paper that if the noise is a sequence of random variables and the noise bound is tight, the optimal sequential outer bounding parallelotope and orthotope do not converge in general although the optimal Sequential Outer bounding ellipsoid converge to a singleton with probability 1.
7 citations
20 Aug 1998
TL;DR: An improved bounding box matching algorithm for detector scoring on synthetic data is presented and a fuzzy knowledge base using the compositional rule of inference with rules generated symmetrically from worth functions is used.
Abstract: How do we judge the goodness of a new pattern recognition technique? The standard approach is to test it on labeled samples. This assumes that we have accurately labeled data. In many imaging applications, that assumption is not so easy to make. In particular, in an Automatic Target Detection system that produces "bounding boxes" for LADAR range images, there is considerable uncertainty deciding if the boxes determined by the algorithm actually correspond to a hit. An improved bounding box matching algorithm for detector scoring on synthetic data is presented. The first modified version uses fuzzy intersection and union operators to combine membership values from multiple matching criteria. The second version uses a fuzzy knowledge base using the compositional rule of inference with rules generated symmetrically from worth functions. Previous mistakes of crisp matching criteria are shown and the improved results of the two new methods are discussed.
6 citations
21 Jun 1995
TL;DR: In this article, the problem of approximating a high-order system with constant real parameter uncertainty by a reduced-order model is considered, and a parameter-dependent quadratic bounding function is developed that bounds the effect of uncertain real parameters on the model-reduction error.
Abstract: The problem of approximating a high-order system with constant real parameter uncertainty by a reduced-order model is considered. A parameter-dependent quadratic bounding function is developed that bounds the effect of uncertain real parameters on the model-reduction error. An auxiliary minimization problem is formulated that minimizes an upper bound for the model-reduction error. The principal result is a necessary condition for solving the auxiliary minimization problem which effectively provides sufficient conditions for characterizing robust reduced-order models.
6 citations
01 Oct 1961-Journal of Research of the National Bureau of Standards Section B Mathematics and Mathematical Physics
TL;DR: In this article, a class of quadratics in finite-dimensional identities of derivatives of integrals to integrals over a smooth bounding surface has been derived for a set of fun ctions.
Abstract: Let R be a simply connected region in E N wi th smooth bounding surface S. For \" sufflciently different iable set of fun ctions we derive a class of quadrat ic in tegral identities r elat in g; surface integrals of derivatives to integrals over R. These identit ies are a genera li zal io ll of a first order iden tity given by L. I-liirmander (Compt. Rend . D ouzieme Congr. des Math6maticiens Scandinaves T enu a Lund, 1953, pp . 105115) and L. E . Payne and H . F . Weinberger (Paci fi c J. Math . (1958) pp . 551573) . As an example of an \" pplicatiolJ of LI1l'sP identi ties we consider a solution u of t he boundar y value prob lem tn< p t< = F in Rand t<= / on S. H ere 6. denotes t he Laplace operator and O~p(x) . We obtain poin twise a priori bounds for t he derivatives of u in R in terms of a quadratic functional of an a rbi trary fu nct ion. H ence t he Rayleigh-Ritz p rocedure can be used to make t he error arbitrari ly slll.ali.
6 citations
TL;DR: It is observed that oriented bounding boxes are not as good as could be expected judging by their extensive use in various applications, and both rectangular- and line-swept spheres are shown to have very good tightness of fit but the line-Swept spheres, or even simple spheres, are shows to be significantly faster because of quick overlap checks.
Abstract: A chain tree is a data structure for representing changing protein conformations. It enables very fast detection of clashes and free potential energy calculations. The efficiency of chain trees is closely related to the bounding volumes associated with chain tree nodes. A protein subchain associated with a node of a chain tree will clash with another subchain only if their bounding volumes intersect. It is therefore essential that bounding volumes are as tight as possible while intersection tests can be carried out efficiently. We compare the performance of four different types of bounding volumes in connection with the rotation of protein bonds. It is observed that oriented bounding boxes are not as good as could be expected judging by their extensive use in various applications. Both rectangular- and line-swept spheres are shown to have very good tightness of fit but the line-swept, or even simple spheres, are shown to be significantly faster because of quick overlap checks. We also investigate how the performance of the recently introduced adjustable chain trees is affected by different bounding volume types.
6 citations