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On the Consistency of the Normalized EightPoint Algorithm
 J MATH IMAGING VIS (2007) 28: 19–27
, 2007
"... A recently proposed argument to explain the improved performance of the eightpoint algorithm that results from using normalized data (Chojnacki, W., et al. in IEEE Trans. Pattern Anal. Mach. Intell. 25(9):1172–1177, 2003) relies upon adoption of a certain model for statistical data distribution. U ..."
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A recently proposed argument to explain the improved performance of the eightpoint algorithm that results from using normalized data (Chojnacki, W., et al. in IEEE Trans. Pattern Anal. Mach. Intell. 25(9):1172–1177, 2003) relies upon adoption of a certain model for statistical data distribution
A Consistency Result for the Normalized EightPoint Algorithm
, 2007
"... A recently proposed argument to explain the improved performance of the eightpoint algorithm that results from using normalized data [IEEE Trans. Pattern Anal. Mach. Intell., 25(9):1172–1177, 2003] relies upon adoption of a certain model for statistical data distribution. Under this model, the cost ..."
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A recently proposed argument to explain the improved performance of the eightpoint algorithm that results from using normalized data [IEEE Trans. Pattern Anal. Mach. Intell., 25(9):1172–1177, 2003] relies upon adoption of a certain model for statistical data distribution. Under this model
Revisiting Hartley's Normalized EightPoint Algorithm
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 2003
"... Abstract — Hartley’s eightpoint algorithm has maintained an important place in computer vision, notably as a means of providing an initial value of the fundamental matrix for use in iterative estimation methods. In this paper, a novel explanation is given for the improvement in performance of the e ..."
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Cited by 16 (4 self)
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of the eightpoint algorithm that results from using normalized data. It is first established that the normalized algorithm acts to minimize a specific cost function. It is then shown that this cost function is statistically better founded than the cost function associated with the nonnormalized algorithm
In Defense of the EightPoint Algorithm
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 1997
"... Abstract—The fundamental matrix is a basic tool in the analysis of scenes taken with two uncalibrated cameras, and the eightpoint algorithm is a frequently cited method for computing the fundamental matrix from a set of eight or more point matches. It has the advantage of simplicity of implementati ..."
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Cited by 203 (1 self)
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Abstract—The fundamental matrix is a basic tool in the analysis of scenes taken with two uncalibrated cameras, and the eightpoint algorithm is a frequently cited method for computing the fundamental matrix from a set of eight or more point matches. It has the advantage of simplicity
Author manuscript, published in "PSIVT, Guanajuato: Mexico (2013)" Singular Vector Methods for Fundamental Matrix Computation
, 2013
"... Abstract. The normalized eightpoint algorithm is broadly used for the computation of the fundamental matrix between two images given a set of correspondences. However, it performs poorly for lowsize datasets due to the way in which the ranktwo constraint is imposed on the fundamental matrix. We p ..."
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Abstract. The normalized eightpoint algorithm is broadly used for the computation of the fundamental matrix between two images given a set of correspondences. However, it performs poorly for lowsize datasets due to the way in which the ranktwo constraint is imposed on the fundamental matrix. We
Planning Algorithms
, 2004
"... This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning, planning ..."
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Cited by 1108 (51 self)
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This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning
The CN2 Induction Algorithm
 MACHINE LEARNING
, 1989
"... Systems for inducing concept descriptions from examples are valuable tools for assisting in the task of knowledge acquisition for expert systems. This paper presents a description and empirical evaluation of a new induction system, cn2, designed for the efficient induction of simple, comprehensib ..."
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Cited by 884 (6 self)
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, comprehensible production rules in domains where problems of poor description language and/or noise may be present. Implementations of the cn2, id3 and aq algorithms are compared on three medical classification tasks.
Factor Graphs and the SumProduct Algorithm
 IEEE TRANSACTIONS ON INFORMATION THEORY
, 1998
"... A factor graph is a bipartite graph that expresses how a "global" function of many variables factors into a product of "local" functions. Factor graphs subsume many other graphical models including Bayesian networks, Markov random fields, and Tanner graphs. Following one simple c ..."
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Cited by 1787 (72 self)
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computational rule, the sumproduct algorithm operates in factor graphs to computeeither exactly or approximatelyvarious marginal functions by distributed messagepassing in the graph. A wide variety of algorithms developed in artificial intelligence, signal processing, and digital communications can
The StructureMapping Engine: Algorithm and Examples
 Artificial Intelligence
, 1989
"... This paper describes the StructureMapping Engine (SME), a program for studying analogical processing. SME has been built to explore Gentner's Structuremapping theory of analogy, and provides a "tool kit" for constructing matching algorithms consistent with this theory. Its flexibili ..."
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Cited by 512 (115 self)
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This paper describes the StructureMapping Engine (SME), a program for studying analogical processing. SME has been built to explore Gentner's Structuremapping theory of analogy, and provides a "tool kit" for constructing matching algorithms consistent with this theory. Its
Efficient Variants of the ICP Algorithm
 INTERNATIONAL CONFERENCE ON 3D DIGITAL IMAGING AND MODELING
, 2001
"... The ICP (Iterative Closest Point) algorithm is widely used for geometric alignment of threedimensional models when an initial estimate of the relative pose is known. Many variants of ICP have been proposed, affecting all phases of the algorithm from the selection and matching of points to the minim ..."
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Cited by 702 (5 self)
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The ICP (Iterative Closest Point) algorithm is widely used for geometric alignment of threedimensional models when an initial estimate of the relative pose is known. Many variants of ICP have been proposed, affecting all phases of the algorithm from the selection and matching of points
Results 1  10
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