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354
OBBTree: A hierarchical structure for rapid interference detection
 Proc. ACM SIGGRAPH, 171–180
, 1996
"... {gottscha,lin,manocha}©cs. unc.edu We present a data structure and an algorithm for efficient and exact interference detection amongst complex models undergoing rigid motion. The algorithm is applicable to all general polygonal and curved models. It precomputes a hierarchical representation of mode ..."
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Cited by 657 (42 self)
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{gottscha,lin,manocha}©cs. unc.edu We present a data structure and an algorithm for efficient and exact interference detection amongst complex models undergoing rigid motion. The algorithm is applicable to all general polygonal and curved models. It precomputes a hierarchical representation of models using tightfitting oriented bounding box trees. At runtime, the algorithm traverses the tree and tests for overlaps between oriented bounding boxes based on a new separating axis theorem, which takes less than 200 operations in practice. It has been implemented and we compare its performance with other hierarchical data structures. In particular, it can accurately detect all the contacts between large complex geometries composed of hundreds of thousands of polygons at interactive rates, almost one order of magnitude faster than earlier methods.
Robust Classification for Imprecise Environments
, 1989
"... In realworld environments it is usually difficult to specify target operating conditions precisely. This uncertainty makes building robust classification systems problematic. We present a method for the comparison of classifier performance that is robust to imprecise class distributions and misclas ..."
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Cited by 253 (14 self)
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In realworld environments it is usually difficult to specify target operating conditions precisely. This uncertainty makes building robust classification systems problematic. We present a method for the comparison of classifier performance that is robust to imprecise class distributions and misclassification costs. The ROC convex hull method combines techniques from ROC analysis, decision analysis and computational geometry, and adapts them to the particulars of analyzing learned classifiers. The method is efficient and incremental, minimizes the management of classifier performance data, and allows for clear visual comparisons and sensitivity analyses. We then show that it is possible to build a hybrid classifier that will perform at least as well as the best available classifier for any target conditions. This robust performance extends across a wide variety of comparison frameworks, including the optimization of metrics such as accuracy, expected cost, lift, precision, recall, and ...
ROC Graphs: Notes and Practical Considerations for Researchers
, 2004
"... Receiver Operating Characteristics (ROC) graphs are a useful technique for organizing classifiers and visualizing their performance. ROC graphs are commonly used in medical decision making, and in recent years have been increasingly adopted in the machine learning and data mining research communitie ..."
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Cited by 225 (1 self)
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Receiver Operating Characteristics (ROC) graphs are a useful technique for organizing classifiers and visualizing their performance. ROC graphs are commonly used in medical decision making, and in recent years have been increasingly adopted in the machine learning and data mining research communities. Although ROC graphs are apparently simple, there are some common misconceptions and pitfalls when using them in practice. This article serves both as a tutorial introduction to ROC graphs and as a practical guide for using them in research.
ROC graphs: Notes and practical considerations for data mining researchers
, 2003
"... Receiver Operating Characteristics (ROC) graphs are a useful technique for organizing classifiers and visualizing their performance. ROC graphs are commonly used in medical decision making, and in recent years have been increasingly adopted in the machine learning and data mining research communitie ..."
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Cited by 157 (0 self)
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Receiver Operating Characteristics (ROC) graphs are a useful technique for organizing classifiers and visualizing their performance. ROC graphs are commonly used in medical decision making, and in recent years have been increasingly adopted in the machine learning and data mining research communities. Although ROC graphs are apparently simple, there are some common misconceptions and pitfalls when using them in practice. This article serves both as a tutorial introduction to ROC graphs and as a practical guide for using them in research. Keywords: 1
GraspIt!  A Versatile Simulator for Robotic Grasping
, 2004
"... Research in robotic grasping has flourished in the last 25 years. A recent survey by Bicchi [1] covered over 140 papers, and many more than that have been published. Stemming from our desire to implement some of the work in grasp analysis for particular hand designs, we created an interactive graspi ..."
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Cited by 93 (15 self)
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Research in robotic grasping has flourished in the last 25 years. A recent survey by Bicchi [1] covered over 140 papers, and many more than that have been published. Stemming from our desire to implement some of the work in grasp analysis for particular hand designs, we created an interactive grasping simulator that can import a wide variety of hand and object models and can evaluate the grasps formed by these hands. This system, dubbed “GraspIt!,” has since expanded in scope to the point where we feel it could serve as a useful tool for other researchers in the field. To that end, we are making the system publicly available (GraspIt! is available for download for a variety of platforms from
How good are convex hull algorithms?
, 1996
"... A convex polytope P can be speci ed in two ways: as the convex hull of the vertex set V of P, or as the intersection of the set H of its facetinducing halfspaces. The vertex enumeration problem is to compute V from H. The facet enumeration problem it to compute H from V. These two problems are esse ..."
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Cited by 81 (8 self)
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A convex polytope P can be speci ed in two ways: as the convex hull of the vertex set V of P, or as the intersection of the set H of its facetinducing halfspaces. The vertex enumeration problem is to compute V from H. The facet enumeration problem it to compute H from V. These two problems are essentially equivalent under point/hyperplane duality. They are among the central computational problems in the theory of polytopes. It is open whether they can be solved in time polynomial in jHj + jVj. In this paper we consider the main known classes of algorithms for solving these problems. We argue that they all have at least one of two weaknesses: inability todealwell with "degeneracies," or, inability tocontrol the sizes of intermediate results. We then introduce families of polytopes that exercise those weaknesses. Roughly speaking, fatlattice or intricate polytopes cause algorithms with bad degeneracy handling to perform badly; dwarfed polytopes cause algorithms with bad intermediate size control to perform badly. We also present computational experience with trying to solve these problem on these hard polytopes, using various implementations of the main algorithms.
Double Description Method Revisited
, 1996
"... . The double description method is a simple and useful algorithm for enumerating all extreme rays of a general polyhedral cone in IR d , despite the fact that we can hardly state any interesting theorems on its time and space complexities. In this paper, we reinvestigate this method, introduce som ..."
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Cited by 75 (2 self)
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. The double description method is a simple and useful algorithm for enumerating all extreme rays of a general polyhedral cone in IR d , despite the fact that we can hardly state any interesting theorems on its time and space complexities. In this paper, we reinvestigate this method, introduce some new ideas for efficient implementations, and show some empirical results indicating its practicality in solving highly degenerate problems. 1 Introduction A pair (A; R) of real matrices A and R is said to be a double description pair or simply a DD pair if the relationship Ax 0 if and only if x = R for some 0 holds. Clearly, for a pair (A; R) to be a DD pair, it is necessary that the column size of A is equal to the row size of R, say d. The term "double description" was introduced by Motzkin et al. [MRTT53], and it is quite natural in the sense that such a pair contains two different descriptions of the same object. Namely, the set P (A) represented by A as P (A) = fx 2 IR d : Ax...
Feature Extraction from Point Clouds
 In Proceedings of the 10 th International Meshing Roundtable
, 2001
"... This paper describes a new method to extract feature lines directly from a surface point cloud. No surface reconstruction is needed in advance, only the inexpensive computation of a neighbor graph connecting nearby points. ..."
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Cited by 55 (0 self)
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This paper describes a new method to extract feature lines directly from a surface point cloud. No surface reconstruction is needed in advance, only the inexpensive computation of a neighbor graph connecting nearby points.
Robust Classification Systems for Imprecise Environments
 In Proceedings of the Fifteenth National Conference on Artificial Intelligence
, 1998
"... In realworld environments it is usually difficult to specify target operating conditions precisely. This uncertainty makes building robust classification systems problematic. We show that it is possible to build a hybrid classifier that will perform at least as well as the best available classifier ..."
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Cited by 50 (4 self)
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In realworld environments it is usually difficult to specify target operating conditions precisely. This uncertainty makes building robust classification systems problematic. We show that it is possible to build a hybrid classifier that will perform at least as well as the best available classifier for any target conditions. This robust performance extends across a wide variety of comparison frameworks, including the optimization of metrics such as accuracy, expected cost, lift, precision, recall, and workforce utilization. In some cases, the performance of the hybrid can actually surpass that of the best known classifier. The hybrid is also efficient to build, to store, and to update. Finally, we provide empirical evidence that a robust hybrid classifier is needed for many realworld problems. Introduction Traditionally, classification systems have been built by experimenting with many different classifiers, comparing their performance and choosing the classifier that performs best....
Collision Detection: Algorithms and Applications
, 1996
"... this paper, we address the first two elements by presenting general a purpose collision detection and contact area determination algorithm for simulations. The collision response is application dependent. The algorithm reports the contact area and thus enables the application to compute an appropria ..."
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Cited by 48 (1 self)
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this paper, we address the first two elements by presenting general a purpose collision detection and contact area determination algorithm for simulations. The collision response is application dependent. The algorithm reports the contact area and thus enables the application to compute an appropriate response. Our algorithm not only addresses interaction between a pair of general polygonal objects, but also large environments consisting of hundreds of moving parts, such as those encountered in the manufacturing plants. Furthermore, we do not assume the motions of the objects to be expressed as a closed form function of time. Our collision detection scheme is efficient and accurate (to the resolution of the models). Given the geometric models, the algorithm precomputes the convex hull and a hierarchical representation of each model in terms of oriented bounding boxes. At runtime, it uses tight fitting axisaligned bounding boxes to pair down the number of object pair interactions to only those pairs within close proximity [12]. For each pair of objects whose bounding boxes overlap, the algorithm checks whether their convex hulls are intersecting based on the closest feature pairs [22]. Finally for each object pair whose convex hulls overlap, it makes use of oriented bounding box hierarchy (OBBTree) to check for actual contact [18]. Organization: The rest of the paper is organized as follows: Section 2 reviews some of the previous work in collision detection. Section 3 outlines the algorithm for pruning the number of object pairs. We briefly describe the closest feature and contact determination algorithms in Section 4. Finally, we describe the imple leftmark