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2,032
Empirical Evaluation of Dissimilarity Measures for Color and Texture
, 1999
"... This paper empirically compares nine image dissimilarity measures that are based on distributions of color and texture features summarizing over 1,000 CPU hours of computational experiments. Ground truth is collected via a novel random sampling scheme for color, and via an image partitioning method ..."
Abstract
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Cited by 247 (6 self)
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This paper empirically compares nine image dissimilarity measures that are based on distributions of color and texture features summarizing over 1,000 CPU hours of computational experiments. Ground truth is collected via a novel random sampling scheme for color, and via an image partitioning method
Dissimilarity Measures in Feature Space
- IEEE ICASSP Montreal Canada
, 2004
"... In this paper, we present a study of the statistical behavior of the dissimilarity measure , proposed in [1] and which results from a machine learning-based quantile estimation approach, namely: single-class support vector machine. This dissimilarity measure possesses the interesting property of ..."
Abstract
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Cited by 2 (2 self)
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In this paper, we present a study of the statistical behavior of the dissimilarity measure , proposed in [1] and which results from a machine learning-based quantile estimation approach, namely: single-class support vector machine. This dissimilarity measure possesses the interesting property
Properties of Binary Vector Dissimilarity Measures
"... This study is to examine the metric or non-metric properties of binary vector dissimilarity measures, on which no comprehensive research has been conducted so far. Especially, the triangle-inequality invariance characterizing several dissimilarity measures is revealed. Moreover, an entropy-based mea ..."
Abstract
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Cited by 7 (1 self)
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This study is to examine the metric or non-metric properties of binary vector dissimilarity measures, on which no comprehensive research has been conducted so far. Especially, the triangle-inequality invariance characterizing several dissimilarity measures is revealed. Moreover, an entropy
A Pixel Dissimilarity Measure That Is Insensitive to Image Sampling
- IEEE Transactions on Pattern Analysis and Machine Intelligence
, 1998
"... Because of image sampling, traditional measures of pixel dissimilarity can assign a large value to two corresponding pixels in a stereo pair, even in the absence of noise and other degrading effects. We propose a measure of dissimilarity that is provably insensitive to sampling because it uses t ..."
Abstract
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Cited by 207 (0 self)
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Because of image sampling, traditional measures of pixel dissimilarity can assign a large value to two corresponding pixels in a stereo pair, even in the absence of noise and other degrading effects. We propose a measure of dissimilarity that is provably insensitive to sampling because it uses
R.: On learning asymmetric dissimilarity measures
- In: Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005), IEEE Computer Society
, 2005
"... Many practical applications require that distance measures to be asymmetric and context-sensitive. We introduce Context-sensitive Learnable Asymmetric Dissimilarity (CLAD) measures, which are defined to be a weighted sum of a fixed number of dissimilarity measures where the associated weights depend ..."
Abstract
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Cited by 2 (0 self)
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Many practical applications require that distance measures to be asymmetric and context-sensitive. We introduce Context-sensitive Learnable Asymmetric Dissimilarity (CLAD) measures, which are defined to be a weighted sum of a fixed number of dissimilarity measures where the associated weights
A Comparison of Rhythmic Dissimilarity Measures
, 2006
"... Measuring the dissimilarity between musical rhythms is a fundamental problem with many applications ranging from music information retrieval and copyright infringement resolution to computational music theory and evolutionary studies of music. A common way to represent a rhythm is as a binary seque ..."
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Measuring the dissimilarity between musical rhythms is a fundamental problem with many applications ranging from music information retrieval and copyright infringement resolution to computational music theory and evolutionary studies of music. A common way to represent a rhythm is as a binary
mp-dissimilarity: A data dependent dissimilarity measure
"... Abstract—Nearest neighbour search is a core process in many data mining algorithms. Finding reliable closest matches of a query in a high dimensional space is still a challenging task. This is because the effectiveness of many dissimilarity measures, that are based on a geometric model, such as `p-n ..."
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Abstract—Nearest neighbour search is a core process in many data mining algorithms. Finding reliable closest matches of a query in a high dimensional space is still a challenging task. This is because the effectiveness of many dissimilarity measures, that are based on a geometric model, such as `p
Comparing dissimilarity measures for content-based image retrieval
"... Abstract. Dissimilarity measurement plays a crucial role in contentbased image retrieval, where data objects and queries are represented as vectors in high-dimensional content feature spaces. Given the large number of dissimilarity measures that exist in many fields, a crucial research question aris ..."
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Cited by 23 (8 self)
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Abstract. Dissimilarity measurement plays a crucial role in contentbased image retrieval, where data objects and queries are represented as vectors in high-dimensional content feature spaces. Given the large number of dissimilarity measures that exist in many fields, a crucial research question
A dissimilarity measure for the ALC description logic
- in Semantic Web Applications and Perspectives, 2nd Italian Semantic Web Workshop SWAP2005
, 2005
"... Abstract. This work presents a dissimilarity measure for an expressive Description Logic endowed with the principal constructors employed in the standard representations for ontological knowledge. In particular, the focus is on the definition of a dissimilarity measure for the ALC description logic ..."
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Cited by 2 (1 self)
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Abstract. This work presents a dissimilarity measure for an expressive Description Logic endowed with the principal constructors employed in the standard representations for ontological knowledge. In particular, the focus is on the definition of a dissimilarity measure for the ALC description logic
Adaptive Histograms And Dissimilarity Measure For Texture Retrieval And Classification
- INTERNATIONAL CONFERENCE ON IMAGE PROCESSING
, 2002
"... Histogram-based dissimilarity measures are extensively used for content-based image retrieval. In an earlier paper [1], we proposed an efficient weighted correlation dissimilarity measure for adaptive-binning color histograms. Compared to existing fixed-binning histograms and dissimilarity measures ..."
Abstract
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Cited by 2 (0 self)
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Histogram-based dissimilarity measures are extensively used for content-based image retrieval. In an earlier paper [1], we proposed an efficient weighted correlation dissimilarity measure for adaptive-binning color histograms. Compared to existing fixed-binning histograms and dissimilarity
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