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2,987
Exploring the Effect of Curvature on the Consistency of Dead Reckoned Paths for Different Error Threshold Metrics
"... Dead reckoning is widely employed as an entity update packet reduction technique in Distributed Interactive Applications (DIAs). Such techniques reduce network bandwidth consumption and thus limit the effects of network latency on the consistency of networked simulations. A key component of the dead ..."
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of the dead reckoning method is the underlying error threshold metric, as this directly determines when an entity update packet is to be sent between local and remote users. The most common metric is the spatial threshold, which is simply based on the distance between a local user’s actual position
Distance metric learning for large margin nearest neighbor classification
 In NIPS
, 2006
"... We show how to learn a Mahanalobis distance metric for knearest neighbor (kNN) classification by semidefinite programming. The metric is trained with the goal that the knearest neighbors always belong to the same class while examples from different classes are separated by a large margin. On seven ..."
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Cited by 695 (14 self)
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We show how to learn a Mahanalobis distance metric for knearest neighbor (kNN) classification by semidefinite programming. The metric is trained with the goal that the knearest neighbors always belong to the same class while examples from different classes are separated by a large margin
Dynamic programming algorithm optimization for spoken word recognition
 IEEE TRANSACTIONS ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING
, 1978
"... This paper reports on an optimum dynamic programming (DP) based timenormalization algorithm for spoken word recognition. First, a general principle of timenormalization is given using timewarping function. Then, two timenormalized distance definitions, ded symmetric and asymmetric forms, are der ..."
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Cited by 788 (3 self)
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to spoken word recognition by different research groups. The experiment shows that the present algorithm gives no more than about twothirds errors, even compared to the best conventional algorithm. categories, a constraint is newly introduced on the warping I.
Loopy belief propagation for approximate inference: An empirical study. In:
 Proceedings of Uncertainty in AI,
, 1999
"... Abstract Recently, researchers have demonstrated that "loopy belief propagation" the use of Pearl's polytree algorithm in a Bayesian network with loops can perform well in the context of errorcorrecting codes. The most dramatic instance of this is the near Shannonlimit performanc ..."
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Cited by 676 (15 self)
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yield accurate posterior marginals in a more general setting than that of error correcting coding the PYRAMID, toyQMR and ALARM networks are quite different from the error correcting coding graphs yet the loopy beliefs show high correlation with the correct marginals. In errorcorrecting codes
Density estimation by wavelet thresholding
 Ann. Statist
, 1996
"... Density estimation is a commonly used test case for nonparametric estimation methods. We explore the asymptotic properties of estimators based on thresholding of empirical wavelet coe cients. Minimax rates of convergence are studied over a large range of Besov function classes Bs;p;q and for a rang ..."
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Cited by 208 (7 self)
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range of global L 0 p error measures, 1 p 0 < 1. A single wavelet threshold estimator is asymptotically minimax within logarithmic terms simultaneously over a range of spaces and error measures. In particular, when p 0> p, some form of nonlinearity is essential, since the minimax linear
Statistical Models for Text Segmentation
 Machine Learning
, 1999
"... . This paper introduces a new statistical approach to automatically partitioning text into coherent segments. The approach is based on a technique that incrementally builds an exponential model to extract features that are correlated with the presence of boundaries in labeled training text. The mode ..."
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Cited by 273 (2 self)
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approach on quantitative and qualitative grounds demonstrates its effectiveness in two very different domains, Wall Street Journal news articles and television broadcast news story transcripts. Quantitative results on these domains are presented using a new probabilistically motivated error metric, which
An Error Metric for Binary Images
, 1992
"... This paper introduces a new error metric for binary images, defined as the pth order mean difference between thresholded distance transforms of the two images. This has a theoretical justification related to topological ideas in mathematical morphology [14, 27, 39] and random set theory [24, 29, 45 ..."
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Cited by 28 (2 self)
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This paper introduces a new error metric for binary images, defined as the pth order mean difference between thresholded distance transforms of the two images. This has a theoretical justification related to topological ideas in mathematical morphology [14, 27, 39] and random set theory [24, 29
A Perceptually Based Physical Error Metric for Realistic Image Synthesis
, 1999
"... We introduce a new concept for accelerating realistic image synthesis algorithms. At the core of this procedure is a novel physical error metric that correctly predicts the perceptual threshold for detecting artifacts in scene features. Built into this metric is a computational model of the human vi ..."
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Cited by 152 (7 self)
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We introduce a new concept for accelerating realistic image synthesis algorithms. At the core of this procedure is a novel physical error metric that correctly predicts the perceptual threshold for detecting artifacts in scene features. Built into this metric is a computational model of the human
Criteria and metrics for thresholded AU detection
"... Implementing a computerized facial expression analysis system for automatic coding requires that a threshold for the system's classffier outputs be selected. However, there are many potential ways to select a threshold. How do different criteria and metrics compare? Manually FACS coded video of ..."
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Implementing a computerized facial expression analysis system for automatic coding requires that a threshold for the system's classffier outputs be selected. However, there are many potential ways to select a threshold. How do different criteria and metrics compare? Manually FACS coded video
Adaptive document image binarization
 PATTERN RECOGNITION
, 2000
"... A new method is presented for adaptive document image binarization, where the page is considered as a collection of subcomponents such as text, background and picture. The problems caused by noise, illumination and many source typerelated degradations are addressed. Two new algorithms are applied t ..."
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Cited by 213 (0 self)
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to determine a local threshold for each pixel. The performance evaluation of the algorithm utilizes test images with groundtruth, evaluation metrics for binarization of textual and synthetic images, and a weightbased ranking procedure for the final result presentation. The proposed algorithms were tested
Results 1  10
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2,987