In some scattered point cloud triangular mesh restoration algorithm, small triangular mesh holes problem will often affect the quality of the model. For small holes at the details, this paper propose a method for iden...
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In some scattered point cloud triangular mesh restoration algorithm, small triangular mesh holes problem will often affect the quality of the model. For small holes at the details, this paper propose a method for identifying and extracting hollow edge,and use a triangle growth way based on boundary edge angle to fill the empty void. First, according the relationship of the point, side and face of the triangle mesh model to identify the hole, then extracting the holes boundary edge and classifying it. Finally, using a triangle growth method based on holes boundary edge angle to fill each small holes separated from the boundary. Compared with other algorithm of filling holes, this method is high efficiency for small holes of smooth surface,and itimprovesthe quality of the triangular mesh model.
In order toovercomethe poor local search ability of genetic algorithm, resulting in the basic genetic algorithm is time-consuming, and low search abilityin the late evolutionary, we use thegray coding instead ofbinary...
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In order toovercomethe poor local search ability of genetic algorithm, resulting in the basic genetic algorithm is time-consuming, and low search abilityin the late evolutionary, we use thegray coding instead ofbinary codingatthebeginning of the coding;we use multi-point crossoverto replace the originalsingle-point ***, theexperimentshows that the improved genetic algorithmnot only has a strong search capability, but also thestability has been effectively improved.
The key frames extraction technique extracts key postures to describe the original motion sequence, which has been widely used in motion compression, motion retrieval, motion edition and so on. In this paper, we propo...
The key frames extraction technique extracts key postures to describe the original motion sequence, which has been widely used in motion compression, motion retrieval, motion edition and so on. In this paper, we propose a method based on the amplitude of curve to find key frames in a motion captured sequence. First we select a group of joint distance features to represent the motion and adopt the Principal Component Analysis (PCA) method to obtain the one dimension principal component as a features curve which will be used. Then we gain the initial key-frames by extracting the local optimum points in the curve. At last, we get the final key frames by inserting frames based on the amplitude of the curve and merging key frames too close. A number of experimental examples demonstrate that our method is practicable and efficient not only in the visual performance but also in the aspect of the compression ratio and error rate.
A network motif is a recurring subnetwork within a network, and it takes on certain functions in practical biological macromolecule applications. Previous algorithms have focused on the computational efficiency of net...
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A network motif is a recurring subnetwork within a network, and it takes on certain functions in practical biological macromolecule applications. Previous algorithms have focused on the computational efficiency of network motif detection, but some problems in storage space and searching time manifested during earlier studies. The considerable computational and spacial complexity also presents a significant challenge. In this paper, we provide a new approach for motif mining based on compressing the searching space. According to the characteristic of the parity nodes, we cut down the searching space and storage space in real graphs and random graphs, thereby reducing the computational cost of verifying the isomorphism of sub-graphs. We obtain a new network with smaller size after removing parity nodes and the "repeated edges" connected with the parity nodes. Random graph structure and sub-graph searching are based on the Back Tracking Method; all sub-graphs can be searched for by adding edges progressively. Experimental results show that this algorithm has higher speed and better stability than its alternatives.
In this paper,the generalized Jacobian matrix and the improved Milne-Hamming linear multi-step prediction and correction algorithm are combined for solving the space manipulator trajectory tracking *** of all,controll...
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In this paper,the generalized Jacobian matrix and the improved Milne-Hamming linear multi-step prediction and correction algorithm are combined for solving the space manipulator trajectory tracking *** of all,controlling end-effector tracks a known trajectory by the method of pseudo inverse of generalized Jacobian ***,due to the accuracy of the solution of this approach inversely with the step-size of numerical integration,we need larger calculation to get more precise *** increase the accuracy in fixed step-size of calculation,Milne-Hamming linear multi-step prediction and correction algorithm is combined with the methods that mentioned ***,we utilize the RungeKutta method to evaluate the first four solutions of MilneHamming algorithm *** don't have enough parameters to initialize the algorithm until step ***,the validity of the algorithm is verified by computer simulation.
Due to the efficient and secure requirements of image transmission, a number of research works have been done to encrypt the compressed image. Inspired by the arithmetic coding and chaotic map which are used to compre...
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Due to the efficient and secure requirements of image transmission, a number of research works have been done to encrypt the compressed image. Inspired by the arithmetic coding and chaotic map which are used to compress and encrypt image, respectively. In this paper, a scheme is proposed to encrypt the compressed image by chaotic map and arithmetic coding. This scheme compresses the image row by row which is firstly permuted by two logistic maps before arithmetic coding. It not only enhances the security of arithmetic coding, but also improves the compression ratio. To further improve the security of binary data which has been compressed, we use the chaotic maps to encrypt the data, and set different parameters and initial value for chaotic maps. In order to possess high sensitivities of key and plain-image, the keys that are employed to determine the parameter and initial value of chaotic maps are related to the plain-image. The experimental results validate the effect of the proposed scheme and demonstrate that the compressed and encrypted image is secure and convenient for transmission.
New image encryption based on DNA encoding combined with chaotic system is proposed. The algorithm uses chaotic system to disturb the pixel locations and pixel values and then DNA encodings according to quaternary cod...
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New image encryption based on DNA encoding combined with chaotic system is proposed. The algorithm uses chaotic system to disturb the pixel locations and pixel values and then DNA encodings according to quaternary code rules are carried out. The pseudo DNA operations are controlled by the quaternary chaotic sequences. At last the image encryption through DNA decoding is achieved. The theoretical analysis and experimental results show that the algorithm improves the encoding efficiency, enhances the security of the ciphertext, has a large key space and a high key sensitivity, it is able to resist the statistical and exhaustive attacks.
In the field of virtual reality, Collision Detection Technology was widely developed for improving the performance of 3D Graphics. Following rapid growth of virtual objects with complex shapes, conventional methods pe...
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In the field of virtual reality, Collision Detection Technology was widely developed for improving the performance of 3D Graphics. Following rapid growth of virtual objects with complex shapes, conventional methods perform harder to effectively detect the collision. Facing the problem, we presented a collision detection algorithm based on improved quantum particle swarm optimization. Firstly, we converted the collision detection problem into nonlinear constrained optimization problem. Secondly, we employed the Euclidean distance to evaluate whether there was collision between two objects. Then, we improved the quantum particle swarm optimization (QPSO) algorithm by (1) using quantum HΕgate and quantum rotation gate in changing quantum probability amplitude, (2) changing the mutation operator with Quantum Hadamard Gate and (3) modifying constant Inertia Weight to random inertia weight. In the end, the results of numerical simulation and analysis were provided to verify the validity of our algorithm.
Large-field high-resolution electron tomography enables visualizing detailed mechanisms under global structure. As field enlarges, the processing time increases and the distortions in reconstruction become more critic...
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Plant growth simulation algorithm (PGSA) is a kind of bionic intelligent optimization algorithm. Based on the plant phototropism as heuristic criterion, this algorithm takes the feasible region of different optimizati...
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