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Mining arbitrary shaped clusters in large data sets is an open challenge in data mining. Various approaches to this problem have been proposed with high time complexity. To save computational cost, some algorithms try to shrink a data set size to a smaller amount of representative data examples. However, their user-defined shrinking ratios may significantly affect the clustering performance. In this...
In this paper we present a new adaptive hybrid surfaces mesh subdivision scheme. Designers often want more flexibility in dealing with both triangles and polygons in their models. With the new subdivision scheme, Catmull-Clark subdivision and Loop subdivision results can be generated, as well as other more flexible surface shapes, by tuning the control parameters we designed. A theorem of C1 is drawn...
This paper considers formation shape control of a team of four agents in the plane, motivated by an example from [1]. We utilize bidirectional, gradient-based interagent distance control laws which are designed so that the agents cooperatively achieve a specified desired formation shape. When every interagent distance is actively controlled (i.e. the information architecture is a complete graph),...
Hierarchical clustering (HC) is a widely used approach both in pattern recognition and data mining and has rich solutions in the literature. But all these existing solutions have some restrictions when the clustered dataset has complex structure. Spectral clustering is a graph-based, simple and outperforming method with the ability to find complex structure in dataset using spectral properties of...
A novel shape similarity measure based on membership function is proposed in this work to make the measure more consistent with human perception and improve the matching accuracy. The proposed method commences with extraction of feature vectors of shapes in training shape set, then a fuzzy set over each eigenvalue space is defined. The membership function of the fuzzy set is defined and acts as a...
In this paper, we provide a method to recognize weed seeds based on computer vision. According to the stability and genetic characteristics described in phytotaxonomy for weed seeds. Image processing method encompasses threshold segmentation and smooth processing etc, nine features parameters are extracted by image processing, which keep RST invariance. The principal components analysis method is...
This paper proposes an index system for the formation performance evaluation of multiple autonomous underwater vehicles (multi-AUV) in deep-sea hydrothermal plume exploration. Firstly the formation evaluation criteria and the essentiality of the application of analytic hierarchy process (AHP) and Fuzzy comprehensive evaluation method (Fuzzy-AHP method) are introduced. Then the index system is established...
In order to detect weak fault eigenfrequency submerged in noises environment, a multitaper-based detection method was developed for incipient motor faults. The tradeoff problem between frequency resolution and variance was studied, and the optimal tradeoff value was chosen to be applied on detecting motor faults. By selecting high energy tapers, the root leakage of eigenfrequency was eliminated, and...
Spherical harmonics are commonly used in the construction of multi-resolution representations of complex spherical shapes such as brain surface meshes. A key step in generating such representations for a spherical mesh is to construct a one-to-one map onto a sphere. A parametrization inevitably introduces local distortions such as stretching and compression, so that some regions can be severely undersampled...
In this paper we develop a new approach of analyzing 3D shapes based on the eigen-system of the Laplace-Beltrami operator. While the eigenvalues of the Laplace-Beltrami operator have been used previously in shape analysis, they are unable to differentiate isospectral shapes. To overcome this limitation, we propose here a new signature based on nodal counts of the eigenfunctions. This signature provides...
In this paper, we consider whether statistical regularities in natural images might be exploited to provide an improved selection criterion for interest points. One approach that has been particularly influential in this domain, is the Harris corner detector. The impetus for the selection criterion for Harris corners, proposed in early work and which remains in use to this day, is based on an intuitive...
This paper proposes an affine invariant matching algorithm for shape correspondence problems in arbitrary dimensions. Formulating shapes by configuration matrices of landmarks, and using the fact that subspaces (e.g. range spaces) of these matrices are invariant to affine transformations, the shape correspondence is modelled as a permutation relation between orthogonal projection matrices of the subspaces...
Surface representation and processing is one of the key topics in computer graphics, since it greatly affects the range of possible applications. This paper reviews the Laplacian operator (differential coordinates) which represent surface's differential geometric properties , discuss the mesh deformation and smoothing based on Laplacian operator. Laplacian operator denotes a vector that is the difference...
We propose a new approach to appearance based loop detection from metric 3D maps, exploiting the NDT surface representation. Locations are described with feature histograms based on surface orientation and smoothness, and loop closure can be detected by matching feature histograms. We also present a quantitative performance evaluation using two real-world data sets, showing that the proposed method...
It has been shown that the least squares boundary residual method can be very efficiently used in radiation problems. Magnetic vector potential is expressed as a linear combination of the wave equation eigenfunctions appropriate for arbitrary shaped antenna. The unknown expansion coefficients follow from minimization of the square error in the boundary condition fulfillment.The boundary condition...
An automated identification technique was developed for the detection of ischemic episodes in long term electrocardiographic (ECG) signals using mathematical expansions involving the discrete dilated Hermite Transform. The discrete Hermite functions are generated as eigenvectors of a symmetric tridiagonal matrix that commutes with the centered Fourier matrix. The Hermite transform values are computed...
This paper presents an effective data analysis approach for character data compression from bi-direction. At the first step of the algorithm, basing on the theory of component analysis, the paper adopt a principal component analysis approach to reduce the dimension of data horizontally, then after comparison of existing clustering algorithms, put forward an immune clustering algorithm based on similarity...
Given a manifold surface M and a continuous scalar function f:Mrarr IR, the Reeb graph of (M, f) is a widely used high-level descriptor of M and its usefulness has been demonstrated for a variety of applications, which range from shape parameterization and abstraction to deformation and comparison. In this context, we propose a novel contouring algorithm for the construction of a discrete Reeb graph...
We present a method for classification and localization of sea mines in 2D side-scan sonar imagery. The approach parallels closely Turk and Pentland's method of eigenfaces and treats mine detection as a two dimensional object recognition and localization problem acknowledging the fact that mine patches are endowed with a measure of regularity in geometry and appearance. We, therefore, set out with...
We have investigated a technique for recognising faces invariant of facial expressions. We apply multi-linear tensor algebra, which subsumes linear algebra, to analyse and recognise 3D face surfaces. This potent framework possesses a remarkable ability to deal with the shortcomings of principle component analysis in less constrained situations. A set of vector spaces can be used to represent the variation...
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