This paper presents a method of camera self-calibration based on structural information of scenes containing isosceles ***,we establish the homography between a plane in the scene and that of an image and provide the ...
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This paper presents a method of camera self-calibration based on structural information of scenes containing isosceles ***,we establish the homography between a plane in the scene and that of an image and provide the expression of the absolute conic in space under an affine coordinates *** using the homography and the constraints of circular points on camera intrinsic parameters,we construct a group of nonlinear equations and determine the camera intrinsic parameters by Levenberg-Marquardt *** experimental results of both synthetic data and real-world data show that our method possesses a high accuracy.
This paper aims to carry out granular analysis of time sequence based on quotient space. Granular methods have long before been adopted to analyze time sequence, but the granularity was based on time, for example, day...
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A novel graph seriation method based random graph theory is proposed in this paper. By seriation processing, graphs can be converted to string through constructing toroidal catch digraph. Seriated graph distance is us...
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A novel graph seriation method based random graph theory is proposed in this paper. By seriation processing, graphs can be converted to string through constructing toroidal catch digraph. Seriated graph distance is using to represent the similarity between graphs. It measures the structural differences between graphs based on the dynamic warping technique. Dynamic time warping distance used in the paper is evaluated by dynamic programming. The results of our experiments demonstrate that the proposed method is eligible for graph distance measure
In this paper, the kurtosis-based method for the classification of mental activities is proposed. The EEG signals were recorded during imagination of left or right hand movement. The kurtosis of EEG and its dynamic pr...
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We present a new distance for the contour-based shapes recognition which we called shape edit distance (SED). Unlike the traditional distance, SED takes into account the spatial deformation of shapes. To compute the s...
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We present a new distance for the contour-based shapes recognition which we called shape edit distance (SED). Unlike the traditional distance, SED takes into account the spatial deformation of shapes. To compute the shape edit distance, we convert shapes to string sequences so that string matching techniques can be used. We pose the problem of string matching as a maximum a posteriori probability (MAP) alignment of the string sequences for shapes and compute the shape edit distance by finding the sequence of string edit operations which minimizes the cost of the path traversing the edit lattice. Experiments demonstrate the utility of the shape edit distance on a number of image retrieval and clustering problems
Principal curve pass througli the middle of a multidimensional data set. to express the distributing shape of the points in the data set, we model principal curve for it. The new method of modeling the complex princip...
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ISBN:
(纸本)9780387446394
Principal curve pass througli the middle of a multidimensional data set. to express the distributing shape of the points in the data set, we model principal curve for it. The new method of modeling the complex principal curve, based on B-spline network, is proposed. This method combines the polygonal line algorithm of learning principal curve with B-spline network. At one time, the algorithm finding a bifurcate point of the complex principal curve is presented. Our experimental results on simulate data demonstrate that it is feasible and effective.
The quotient space theory is indented to study the relationship of transform and that of dependency among the worlds with different grain-size. Compared-with other granule computing tools, it has more powerful abiliti...
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ISBN:
(纸本)9781424404759
The quotient space theory is indented to study the relationship of transform and that of dependency among the worlds with different grain-size. Compared-with other granule computing tools, it has more powerful abilities of representation and absorption. The reason is that structure is introduced in its model The paper is to study the quotient space theory based on structure. We first introduce some methods of constructing quotient structure. Then we study in detail the quotient space family based on structure, and get some good results for further research. Finally we also briefly discuss hierarchical structure of fuzzy sets.
In this paper, we offers a new algebraic point of view for DNA molecules and introduce the algebraic system by using the natural operation based on the Sigma = {A, C, G, T} . We characterize its structure by using the...
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In this paper, we offers a new algebraic point of view for DNA molecules and introduce the algebraic system by using the natural operation based on the Sigma = {A, C, G, T} . We characterize its structure by using the algebraic theory. We show that (L, oplus, otimes ) is the distribution lattice of rings with identical element. Furthermore,we generalize this result to the Wrho(V) , a set which elements simulates the DNA molecules with sticky ends, the element is called an incomplete double stranded molecules consist of mixed DNA molecules with double and single strands.
This paper investigates the spectral description methods for unweighted graph sequences and the clustering of spectral features in feature spaces. First, the corner features in 2D images of 3D polyhedral objects are r...
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This paper investigates the spectral description methods for unweighted graph sequences and the clustering of spectral features in feature spaces. First, the corner features in 2D images of 3D polyhedral objects are represented as neighborhood graphs. Adjacency matrices are constructed from Delaunay graphs of the corners. Then the eigenmodes are defined by the leading eigenvectors of the adjacency matrices. For each eigenmode, we compute the vectors of spectral properties, which include the eigenmode perimeter, eigenmode volume, Cheeger number, inter-mode adjacency matrix and inter-mode edge distance. Then these vectors are embedded into a pattern space by multidimensional scaling on the L2 norm for pairs of pattern vectors. Meanwhile, the performances of different embedding methods are compared. Finally, the clustering results by k-means method are shown
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