The formal model of spatial directional relations is one of the most important parts in spatial relation research. The most of models are based on Minimum Bounding Rectangle (MBR), and they are not compliant with the ...
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The formal model of spatial directional relations is one of the most important parts in spatial relation research. The most of models are based on Minimum Bounding Rectangle (MBR), and they are not compliant with the regular pattern of human cognition. In order to get a closer conclusion to human cognition on directional relationship, Angle Histogram model based on Double-projection and Rounded-subdivision (AHDPRS) is proposed in this paper. The model uses the maximum inscribed circles to find out the maximum parts of the object, and calculates the directional relationship between the centers of the circles. This model ignores the inessential details to ensure the result which will be closer to human cognition. The experiments show that this model is feasible.
Since the SIFT feature point extraction algorithm with scale changes, rotation transformation invariance, is widely used in image registration. In this paper, the SIFT algorithm is applied to three-dimensional point c...
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Since the SIFT feature point extraction algorithm with scale changes, rotation transformation invariance, is widely used in image registration. In this paper, the SIFT algorithm is applied to three-dimensional point cloud coarse registration, the proposed 3DSIFT extraction algorithm is suitable for three-dimensional point cloud data, then point coordinates, curvature, the nearest neighbor distance mean and other information compose fourteen-dimensional vector to conduct correspondence match, use the interior point rate of Ransac to obtain optimal transformation, and finally transform the coordinates for source point clouds using the optimal transform, complete the point cloud data coarse registration. Experimental results show that our coarse registration algorithm can effectively extract feature points, and it is robust for the point cloud with noisy point, it can provide accurate and effective initial value for the precise registration such as ICP.
In the high-dimensional data traditional clustering algorithms tend to break down because of the curse of dimensionality, high cost of time, etc. This paper proposes a novel algorithm AReSUBCLU, an Effective Subspace ...
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In order to effectively eliminate outliers and noise points in 3D scattered point cloud, a denoising smoothing algorithm which is the combination of removing outliers algorithm and trilateral filter is proposed. This ...
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In this paper, we propose a method based on the Weber number to uniformly model and simulate the foam and sprays generated by the fluid motion. We use the SPH to construct the fluid and calculate the Weber number of e...
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A collision detection algorithm based on capsule bounding volume (CBV for short) is presented improve the efficiency of Collision detection in three-dimensional scene. This algorithm use CBV to encircle roles and achi...
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In this paper, we focus on efficient processing of XML keyword queries based on smallest lowest common ancestor （SLCA） semantics. For a given query Q with m keywords, we propose to use stable matches as the basis fo...
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In this paper, we focus on efficient processing of XML keyword queries based on smallest lowest common ancestor （SLCA） semantics. For a given query Q with m keywords, we propose to use stable matches as the basis for SLCA computation, where each stable match M consists of m nodes that belong to the m distinct keyword inverted lists of Q. M satisfies that no other lowest common ancestor （LCA） node of Q can be found to be located after the first node of M and be a descendant of the LCA of M, based on which the operation of locating a stable match can skip more useless nodes. We propose two stable match based algorithms for SLCA computation, i.e., BSLCA and HSLCA. BSLCA processes two keyword inverted lists each time from the shortest to the longest, while HSLCA processes all keyword inverted lists in a holistic way to avoid the problem of redundant computation invoked by BSLCA. Our extensive experimental results verify the performance advantages of our methods according to various evaluation metrics.
Detecting community structure based on node similarity cost lower time complexity, but they ignore the indirect relationships of nodes. We proposed an improved algorithm for detecting community structure based on node...
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A novel method based on multilevel meshes is proposed to simulate the cloth draping process rapidly on a complex model. Considering of the difficulty of computing the realtime collision between cloth and complex model...
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In order to solve the overload problem of root ONS in the EPC network, a load balancing algorithm based on multi-root ONS is proposed. Based on the proposed load balancing ONS (LB ONS) architecture, the ONS Root is de...
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