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128,313
Footprint evaluation for volume rendering
 Computer Graphics
, 1990
"... This paper presents a forward mapping rendering algorithm to display regular volumetric grids that may not have the same spacings in the three grid directions. It takes advantage of the fact that convolution can be thought of as distributing energy from input samples into space. The renderer calcul ..."
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Cited by 504 (1 self)
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This paper presents a forward mapping rendering algorithm to display regular volumetric grids that may not have the same spacings in the three grid directions. It takes advantage of the fact that convolution can be thought of as distributing energy from input samples into space. The renderer
A comparison and evaluation of multiview stereo reconstruction algorithms
 In IEEE CVPR
, 2006
"... This paper presents a quantitative comparison of several multiview stereo reconstruction algorithms. Until now, the lack of suitable calibrated multiview image datasets with known ground truth (3D shape models) has prevented such direct comparisons. In this paper, we rst survey multiview stereo a ..."
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Cited by 533 (15 self)
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This paper presents a quantitative comparison of several multiview stereo reconstruction algorithms. Until now, the lack of suitable calibrated multiview image datasets with known ground truth (3D shape models) has prevented such direct comparisons. In this paper, we rst survey multiview stereo algorithms and compare them qualitatively using a taxonomy that differentiates their key properties. We then describe our process for acquiring and calibrating multiview image datasets with highaccuracy ground truth and introduce our evaluation methodology. Finally, we present the results of our quantitative comparison of stateoftheart multiview stereo reconstruction algorithms on six benchmark datasets. The datasets, evaluation details, and instructions for submitting new models are available online at
Mean shift, mode seeking, and clustering
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 1995
"... AbstractMean shift, a simple iterative procedure that shifts each data point to the average of data points in its neighborhood, is generalized and analyzed in this paper. This generalization makes some kmeans like clustering algorithms its special cases. It is shown that mean shift is a modeseeki ..."
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Cited by 620 (0 self)
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AbstractMean shift, a simple iterative procedure that shifts each data point to the average of data points in its neighborhood, is generalized and analyzed in this paper. This generalization makes some kmeans like clustering algorithms its special cases. It is shown that mean shift is a modeseeking process on a surface constructed with a “shadow ” kernel. For Gaussian kernels, mean shift is a gradient mapping. Convergence is studied for mean shift iterations. Cluster analysis is treated as a deterministic problem of finding a fixed point of mean shift that characterizes the data. Applications in clustering and Hough transform are demonstrated. Mean shift is also considered as an evolutionary strategy that performs multistart global optimization. Index TermsMean shift, gradient descent, global optimization, Hough transform, cluster analysis, kmeans clustering. I.
A Fast Algorithm for Particle Simulations
, 1987
"... this paper to the case where the potential (or force) at a point is a sum of pairwise An algorithm is presented for the rapid evaluation of the potential and force fields in systems involving large numbers of particles interactions. More specifically, we consider potentials of whose interactions a ..."
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Cited by 1145 (19 self)
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this paper to the case where the potential (or force) at a point is a sum of pairwise An algorithm is presented for the rapid evaluation of the potential and force fields in systems involving large numbers of particles interactions. More specifically, we consider potentials of whose interactions are Coulombic or gravitational in nature. For a the form system of N particles, an amount of work of the order O(N 2 ) has traditionally been required to evaluate all pairwise interactions, un F5F far 1 (F near 1F external ), less some approximation or truncation method is used. The algorithm of the present paper requires an amount of work proportional to N to evaluate all interactions to within roundoff error, making it where F near (when present) is a rapidly decaying potential con
Toward an instance theory of automatization
 Psychological Review
, 1988
"... This article presents a theory in which automatization is construed as the acquisition of a domainspecific knowledge base, formed of separate representations, instances, of each exposure to the task. Processing is considered automatic if it relies on retrieval of stored instances, which will occur ..."
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Cited by 613 (37 self)
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This article presents a theory in which automatization is construed as the acquisition of a domainspecific knowledge base, formed of separate representations, instances, of each exposure to the task. Processing is considered automatic if it relies on retrieval of stored instances, which will occur only after practice in a consistent environment. Practice is important because it increases the amount retrieved and the speed of retrieval; consistency is important because it ensures that the retrieved instances will be useful. The theory accounts quantitatively for the powerfunction speedup and predicts a powerfunction reduction in the standard deviation that is constrained to have the same exponent as the power function for the speedup. The theory accounts for qualitative properties as well, explaining how some may disappear and others appear with practice. More generally, it provides an alternative to the modal view of automaticity, arguing that novice performance is limited by a lack of knowledge rather than a scarcity of resources. The focus on learning avoids many problems with the modal view that stem from its focus on resource limitations. Automaticity is an important phenomenon in everyday mental life. Most of us recognize that we perform routine activities quickly and effortlessly, with little thought and conscious awarenessin short, automatically (James, 1890). As a result, we often perform those activities on "automatic pilot " and turn our minds to other things. For example, we can drive to dinner while conversing in depth with a visiting scholar, or we can make coffee while planning dessert. However, these benefits may be offset by costs. The automatic pilot can lead us astray, causing errors and sometimes catastrophes (Reason & Myceilska, 1982). If the conversation is deep enough, we may find ourselves and the scholar arriving at the office rather than the restaurant, or we may discover that we aren't sure whether we put two or three scoops of coffee into the pot. Automaticity is also an important phenomenon in skill acquisition (e.g., Bryan & Harter, 1899). Skills are thought to consist largely of collections of automatic processes and procedures
LucasKanade 20 Years On: A Unifying Framework: Part 3
 International Journal of Computer Vision
, 2002
"... Since the LucasKanade algorithm was proposed in 1981 image alignment has become one of the most widely used techniques in computer vision. Applications range from optical flow, tracking, and layered motion, to mosaic construction, medical image registration, and face coding. Numerous algorithms hav ..."
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Cited by 698 (30 self)
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Since the LucasKanade algorithm was proposed in 1981 image alignment has become one of the most widely used techniques in computer vision. Applications range from optical flow, tracking, and layered motion, to mosaic construction, medical image registration, and face coding. Numerous algorithms have been proposed and a variety of extensions have been made to the original formulation. We present an overview of image alignment, describing most of the algorithms in a consistent framework. We concentrate on the inverse compositional algorithm, an efficient algorithm that we recently proposed. We examine which of the extensions to the LucasKanade algorithm can be used with the inverse compositional algorithm without any significant loss of efficiency, and which cannot. In this paper, Part 3 in a series of papers, we cover the extension of image alignment to allow linear appearance variation. We first consider linear appearance variation when the error function is the Euclidean L2 norm. We describe three different algorithms, the simultaneous, project out, and normalization inverse compositional algorithms, and empirically compare them. Afterwards we consider the combination of linear appearance variation with the robust error functions described in Part 2 of this series. We first derive robust versions of the simultaneous and normalization algorithms. Since both of these algorithms are very inefficient, as in Part 2 we derive efficient approximations based on spatial coherence. We end with an empirical evaluation of the robust algorithms.
Linear pattern matching algorithms
 IN PROCEEDINGS OF THE 14TH ANNUAL IEEE SYMPOSIUM ON SWITCHING AND AUTOMATA THEORY. IEEE
, 1972
"... In 1970, Knuth, Pratt, and Morris [1] showed how to do basic pattern matching in linear time. Related problems, such as those discussed in [4], have previously been solved by efficient but suboptimal algorithms. In this paper, we introduce an interesting data structure called a bitree. A linear ti ..."
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Cited by 549 (0 self)
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In 1970, Knuth, Pratt, and Morris [1] showed how to do basic pattern matching in linear time. Related problems, such as those discussed in [4], have previously been solved by efficient but suboptimal algorithms. In this paper, we introduce an interesting data structure called a bitree. A linear time algorithm for obtaining a compacted version of a bitree associated with a given string is presented. With this construction as the basic tool, we indicate how to solve several pattern matching problems, including some from [4], in linear time.
TnT  A Statistical PartOfSpeech Tagger
, 2000
"... Trigrams'n'Tags (TnT) is an efficient statistical partofspeech tagger. Contrary to claims found elsewhere in the literature, we argue that a tagger based on Markov models performs at least as well as other current approaches, including the Maximum Entropy framework. A recent comparison h ..."
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Cited by 525 (5 self)
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Trigrams'n'Tags (TnT) is an efficient statistical partofspeech tagger. Contrary to claims found elsewhere in the literature, we argue that a tagger based on Markov models performs at least as well as other current approaches, including the Maximum Entropy framework. A recent comparison has even shown that TnT performs significantly better for the tested corpora. We describe the basic model of TnT, the techniques used for smoothing and for handling unknown words. Furthermore, we present evaluations on two corpora.
A Maximum Entropy Model for PartOfSpeech Tagging
, 1996
"... This paper presents a statistical model which trains from a corpus annotated with PartOfSpeech tags and assigns them to previously unseen text with stateoftheart accuracy(96.6%). The model can be classified as a Maximum Entropy model and simultaneously uses many contextual "features" t ..."
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Cited by 577 (1 self)
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This paper presents a statistical model which trains from a corpus annotated with PartOfSpeech tags and assigns them to previously unseen text with stateoftheart accuracy(96.6%). The model can be classified as a Maximum Entropy model and simultaneously uses many contextual "features" to predict the POS tag. Furthermore, this paper demonstrates the use of specialized features to model difficult tagging decisions, discusses the corpus consistency problems discovered during the implementation of these features, and proposes a training strategy that mitigates these problems.
An Extended Set of Fortran Basic Linear Algebra Subprograms
 ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE
, 1986
"... This paper describes an extension to the set of Basic Linear Algebra Subprograms. The extensions are targeted at matrixvector operations which should provide for efficient and portable implementations of algorithms for high performance computers. ..."
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Cited by 526 (72 self)
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This paper describes an extension to the set of Basic Linear Algebra Subprograms. The extensions are targeted at matrixvector operations which should provide for efficient and portable implementations of algorithms for high performance computers.
Results 1  10
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