Showing papers on "Bounding overwatch published in 2000"

Optimized bounding boxes for three-dimensional treatment planning in brachytherapy

Abstract: It is sometimes necessary to determine the optimal value for a direction dependent quantity. Using a search technique based on Powell’s quadratic convergent method such an optimal direction can be approximated. The necessary geometric transformations in n-dimensional space are introduced. As an example we consider the approximation of the minimum bounding box of a set of three-dimensional points. Minimum bounding boxes can significantly improve accuracy and efficiency of the calculations in modern brachytherapytreatment planning of the volumes of objects or the dose distribution inside an object. A covariance matrix based approximation method for the minimum bounding box is compared with the results of the search method. The benefits of the use of optimal oriented bounding boxes in brachytherapytreatment planning systems are demonstrated and discussed.

Shape sensitive geometric complexity

Abstract: The traditional algorithm analysis for geometric problems has focused on worst-case asymptotic complexity. Such analyses have often concluded that certain simple algorithms are worthless because they have poor worst-case performance. However, empirical experience shows that these algorithms tend to perform very well in practice. How does one explain this disparity? This dissertation uses shape sensitive analysis to explores this phenomenon by investigating two problems: the use of bounding boxes in collision detection, and the complexity of geometric permutations in visibility computation. Bounding boxes are used widely in computer graphics as simple approximations of complex objects. Because of their simpler shape, computing with boxes is almost always easier and faster than with the original objects. Experience has shown that the use of bounding boxes greatly improves the performance of geometric algorithms in collision detection, rendering and modeling. However, the goal of proving that bounding boxes maintain high performance in the worst case has remained elusive. In fact, traditional analysis of algorithms has concluded that in the worst-case bounding boxes add nothing but overhead. We will show how to reconcile this discrepancy using shape-sensitive analysis. Our proof shows that the performance of bounding boxes depends on two natural shape parameters of objects, and the observed efficiency of boxes can be attributed to the fact that objects in practice tend to have small values of these parameters. The second part of this thesis focuses on the complexity of geometric permutations. Geometric permutations are a natural analog of the more familiar numerical permutation. Given a set of disjoint convex bodies in some fixed d-dimensional space, a geometric permutation is the order in which these objects can be intersected by a line. We will be interested in the “combinatorics” of such permutations—namely, given n objects in d-space, how many combinatorially distinct geometric permutations are possible. Our breakthrough result is that a set of n unit balls in Rd admits at most a constant number of geometric permutations. The constant bound significantly improves upon the Θ(n d−1) bound for the balls of arbitrary radii. Intrigued by this large gap between the two bounds, we then study how the number of geometric permutations varies as a function of shape, size, and spacing of objects.

Adaptive optimal bounded-ellipsoid identification with an error under-bounding safeguard: applications in state estimation and speech processing

Abstract: Optimal bounding ellipsoid (OBE) identification algorithms are noted for their simplicity and ability to leverage model error-bound knowledge for improved parameter convergence. However, the OBE convergence rate is dependent on the pointwise "tightness" of the model error-bound estimates. Since the least upper bound on the model error is often unknown, the convergence rate is compromised by the need to overestimate error-bounds lest the integrity of the process be violated by underestimation. We present an effective under-bounding safeguard against system model violations in OBE processing. Simulation examples in state estimation and speech processing demonstrate the efficacy of the under-bounding safeguard.

Method for generating minimum bounding area of multidimensional space retrieval, method for minimum bounding sphere encoding, structure, updating method, and searching method for multidimensional space data, and program implementing the methods

Abstract: PROBLEM TO BE SOLVED: To generate a minimum bounding area including a minimum bounding sphere by detecting the partial space of a master node where the center point of a minimum bounding sphere of a slave node is present and calculating the Minkowski sum of the partial space where the center point of the minimum bounding sphere of the slave node is present and the minimum bounding sphere of the slave node. SOLUTION: For example, a bounding rectangular A and a sphere C having its center point at a point B are present in an n-dimensional space and B is included in A. In this case, a rectangle Vb is a virtual bounding rectangle(VBR). At this time, a geometric object Vc represented by the Minkowski sum of C and Vb is called a virtual bounding quasisphere(VBS). There, the minimum bounding area of the master node is divided into 2n partial spaces and the partial space of the master node where the center point of the minimum bounding sphere of the slave node is present is detected. Then the Minkowski sum of the partial space where the center point of the minimum bounding sphere of the slave node and the minimum bounding sphere of the slave node is calculated to generate a minimum bounding area including the minimum bounding sphere.

Method of managing database by using divided minimum bounding rectangle

Abstract: PURPOSE: A method of managing database is provided to improve an efficiency of space inquiry processing by performing a calculating exterior boundaries of a specified objective and a sub-objective. CONSTITUTION: The method of managing database is comprising the steps of calculating two sub-objectives by dividing a minimum bounding rectangle(MBR) region surrounding a space objective, creating a decomposed minimum bounding rectangle(DMBR) divided against each sub-objective calculated, shifting each coordinate axis by turns repeatedly until the decomposed minimum bounding rectangles are satisfied with a limit condition expressed by accuracy of the decomposition(AOD), dividing repeatedly if the size of the decomposed minimum bounding rectangle surpasses a predetermined limit value. In method of managing database, user can choose the optimum value between the number of composing elements and complicity by controlling the number of composing elements depend on a given limit condition.

Tree-based search for ECVQ

Abstract: Summary form only given. We propose two new tree-based search algorithms for vector quantizers using an additive weighted distance measure, such as ECVQ (entropy constrained vector quantization) (Chou et al., 1989). Both algorithms are based on a recursive space division technique, and use a bounding object at each node of the tree, in order to quickly eliminate subsets of the codebook during the search. The structure is more general than the k-d tree and the algorithm performs an optimal search similar to the one analyzed by Berchtold et al. (1997). We prove a theorem that defines the necessary and sufficient condition for any set of points to be a valid bounding object, i.e. to define a lossless pruning rule for the additive weighed Euclidean distance. The first algorithm presented uses rectangles as bounding objects, and the other uses spheres. We experimentally compare our approach with another recent one (Johnson et al., 1996), and show that the new algorithm using bounding rectangles performs significantly better for medium and high bitrate coding (>0.1 bits/sample) of a Gaussian process. This algorithm uses approximately 29 times less multiplications than a full codebook search at 1 bits/sample.

Form analysis of particles using a parametric transform

Abstract: A method of analysing the form of an object, the method comprising using a parametric transform to generate bounding curve data in a transform space, the bounding curve data being representative of a convex hull of the object, and using the bounding curve data to identify points on the object which are most likely to contact an opposing surface.

Study and comparison of membership-set outer bounding

Abstract: When model output-error is unknown but bounded, the set of parameter called the membership-set and consistent with the measurement, the model and the error bounds is a polytope, the complexity of which is increasing with the model order and the measurement number. Such complexity bereaves the algorithm updating the polytope to be used in real time control. To overcome this complexity, the exact polytope is approximated by an outer bounding region with a simpler shape and which approximate it as most as possible. In this paper we present first algorithms which update the exact polytope and its outer bounding approximations such as ellipsoid, parallelotope or orthotope. A comparative study of these algorithms is carried out. The comparison is based on the volume of the final region, the computing and the convergence times, the numerical complexity and the updating rate.

Bounding Predicates and Insertion Policies for Multidimensional Indexes

Abstract: We present two new techniques for improving the performance of multidimensional indexes. For static data sets, we find that bulk loading techniques are effective at clustering data items in the index; however, traditional designs of an index''s bounding predicates can lead to poor performance. We develop and implement in GiST three new bounding predicates, two of which have much better performance characteristics for our Blobworld image-search application than several traditional access methods. We then proceed to study dynamic data sets, the analysis of which lead to a focus on insertion algorithms. We develop, implement, and analyze an insertion algorithm called the Aggressive Insertion Policy, which uses global rather than greedy information when making insertion decisions.

Using adaptive bounding in voltage security analysis

Abstract: This paper provides the framework of using an adaptive bounding method in online voltage security analysis. The control relationships between the voltage performance in a voltage control area and the local reactive support are emphasized. The area of interest is adaptively bounded with the indication of electrical distance. Heuristic rules are applied to classify the contingencies into different potential voltage instability types.

SinusCone /spl Theta//spl Phi/-a ThetaPhi algorithm for human arm animation

Abstract: Arm animation algorithms are often categorized by their constraint expansion strategy. One option is the geometric bounding polygon-cone strategy, a simple containment search strategy that traverses the search space in the order in which successor bounding polygon edges are generated. An alternative is the ThetaPhi-cone strategy, which was designed to make it possible to use domain-specific heuristic information. By exploring promising parts of the cone space first, ThetaPhi-cone algorithms generally are more efficient than polygon-cone algorithms.