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Physical Sciences and Mathematics

Journal of System Simulation

Journal

Feature extraction

Publication Year

Articles 1 - 11 of 11

Full-Text Articles in Engineering

3d Streamline Visualization Method Based On Clustering Fusion, Xuqiang Shao, Ya Cheng, Yizhong Jin Mar 2024

3d Streamline Visualization Method Based On Clustering Fusion, Xuqiang Shao, Ya Cheng, Yizhong Jin

Journal of System Simulation

Abstract: In order to solve the problems of incomplete feature extraction, continuity destruction of flow field by visual results, and poor representation of streamline caused by unstable clustering division when the clustering method is used to realize 3D streamline visualization. A 3D streamline visualization method based on clustering fusion is proposed. It consists of a distance measurement method between features and a clustering fusion method, which takes the inter-feature distance and spatial distance as the similarity between streamlines for clustering and then performs weighted merging and subdivision of the obtained clustering result. The method has been tested on data sets …


Engine Wear Fault Diagnosis Based On Supervised Kernel Entropy Component Analysis, Zhichao Zhu, Dinghui Wu, Yuanchang Yue Jan 2022

Engine Wear Fault Diagnosis Based On Supervised Kernel Entropy Component Analysis, Zhichao Zhu, Dinghui Wu, Yuanchang Yue

Journal of System Simulation

Abstract: Focus on the influence of environment on engine operation, which leads to a large amount of redundant information and nonlinear structure in oil spectral data that affects the engine fault diagnosis results, the feature extraction method of SKECA (supervised kernel entropy component analysis) is proposed. A supervised learning algorithm is adopted on the basis of Kernel Entropy Component Analysis, which extracts the inherent geometric features of oil spectrum data to make the extracted fault features include the discriminative information. GA (genetic algorithm) is used to find parameters to optimize the results of feature extraction, and SVM (support vector machine) …


Study On Hand Gesture Recognition And Portfolio Optimization Model Based On Svm, Zhiwei Cai, Shuyan Wu, Junfeng Song Aug 2020

Study On Hand Gesture Recognition And Portfolio Optimization Model Based On Svm, Zhiwei Cai, Shuyan Wu, Junfeng Song

Journal of System Simulation

Abstract: Hand gesture recognition was researched. The idea of extracting related features was proposed by using SVM algorithm in machine learning domain, and combination optimization method was used, which consists of ANN, HMM and DTW, to do hand gesture recognition. The experimental results show that portfolio optimization model based gesture recognition method has high accuracy and is very effective.


Heat Kernel Signature Extraction Algorithm Based On Mesh Simplification, Haisheng Li, Sun Li, Cai Qiang, Cao Jian Aug 2020

Heat Kernel Signature Extraction Algorithm Based On Mesh Simplification, Haisheng Li, Sun Li, Cai Qiang, Cao Jian

Journal of System Simulation

Abstract: Heat kernel signature has been proposed for 3D model feature extraction in recent years. However, the performance of heat kernel signature is inefficient, especially when the models have large number of vertices. Mesh simplification algorithm based on quadric error metrics was used to preprocess 3D model and the heat kernel signature was calculated based on the simplified model. Experiments show that the feature extracting time of the simplified model is less than the original model. The more vertices of the original model, the more obvious of the improved efficiency. The heat kernel signature of simplified model is consistent with …


Improved Method Of Extracting Hks Descriptors And Non-Rigid Classification Applications, Jingyu Jiang, Lili Wan Aug 2020

Improved Method Of Extracting Hks Descriptors And Non-Rigid Classification Applications, Jingyu Jiang, Lili Wan

Journal of System Simulation

Abstract: In order to make the HKS(heat kernel signature)have wider applicability in non-rigid shape analysis, an improved method of extracting HKS descriptors for unconnected non-rigid 3D models was proposed. The largest connected component was obtained. The HKS descriptors of the largest connected component were calculated and those descriptors of the boundary vertices and their 1-ring neighbors were excluded. For shape classifications, the dictionary was learned for each class based on the sparse representation theory. For a test model, each dictionary was utilized to sparsely represent its descriptor set, and the most appropriate dictionary was determined by the representation error, …


Research Of Merging Three-Dimensional Static Scene And Moving Objects Based On Video, Kunjin He, Wang Lin, Jianxin Liu, Zhengming Chen, Xiaozhong Chen Jul 2020

Research Of Merging Three-Dimensional Static Scene And Moving Objects Based On Video, Kunjin He, Wang Lin, Jianxin Liu, Zhengming Chen, Xiaozhong Chen

Journal of System Simulation

Abstract: Against the difficulty in three-dimensional real-time rendering of scene that contains moving objects, a video-based method in building and merging three-dimensional static scene and moving objects was proposed. According to the classification of moving objects, a three-dimensional static scene was established and a parameterized model base was produced. Based on the video, moving objects were detected and features (including basic features and dynamic features) were extracted. Based on basic features, corresponding type model in the parameterized model base was instantiated. Based on the dynamic features, the three-dimensional static scene and moving object models were merged and the …


Research On Simulation Of Multi-Target Micro-Doppler Separation And Extraction In Ballistic Midcourse, Yizhe Wang, Cunqian Feng, Jingqing Li Jun 2020

Research On Simulation Of Multi-Target Micro-Doppler Separation And Extraction In Ballistic Midcourse, Yizhe Wang, Cunqian Feng, Jingqing Li

Journal of System Simulation

Abstract: Aiming at the intricate overlap and difficult separation and extraction of micro-Doppler information in Doppler spectra of warheads and fragments in midcourse, a novel method based on CEEMD and improved self-adaptive Viterbi algorithm was proposed. By analyzing the differences of micro-Doppler distribution between warheads and fragments, the echo was decomposed by CEEMD and each IMF was denoised by wavelet threshold denoising method, resulting in separation of warheads and fragments echo. The fragments signal was stretched, the optimal path was extracted combined with improved self-adaptive Viterbi algorithm, and the separation of multi-target signal and extraction of micro-Doppler was realized. Simulation …


Motion Object Feature Extraction Method Based On Multi-Feature Fusion, Xidao Luan, Yuxiang Xie, Zhang Xin, Niu Xiao Jun 2020

Motion Object Feature Extraction Method Based On Multi-Feature Fusion, Xidao Luan, Yuxiang Xie, Zhang Xin, Niu Xiao

Journal of System Simulation

Abstract: Motion object feature extraction is the basis of motion object classification. Traditionally motion object classification mainly depends on single feature extraction which is sensitive to the aspects like motion object detection area, angle, scale and noise disturbance, thus decreases the classification efficiency. To solve these problems and improve the robustness of the algorithms, a motion object feature extraction method based on multi-feature fusion was proposed. In this method, width height ratio feature, rotation invariant uniform local binary pattern feature and SIFT feature were considered, and by fusing them into the SVM and KNN classifier, motion object classification was carried …


Multi-Pose Pedestrian Detection Based On Posterior Multiple Sparse Dictionaries, Lingkang Gu, Mingzheng Zhou, Wang Jun, Xiu Yu Jun 2020

Multi-Pose Pedestrian Detection Based On Posterior Multiple Sparse Dictionaries, Lingkang Gu, Mingzheng Zhou, Wang Jun, Xiu Yu

Journal of System Simulation

Abstract: In order to detect pedestrians effectively, a multi-pose pedestrian detection method based on posterior multiple sparse dictionaries was proposed. Through pre-learning multiple different sparse dictionaries, and sparse coding the image, statistics for each dictionary corresponds to sparse coding histogram as the pedestrian image feature descriptor. The common information of multiple sparse dictionary features of all positive samples was obtained, and the feature of a single pedestrian sample was weighted, and the features of a posteriori multiple sparse dictionary could be obtained. Then pedestrians of different poses and views were divided into subclasses with clustering algorithm. A classifier was trained …


Research On Augmented Reality Method Based On Unmarked Recognition, Li Qian, Shangbing Gao, Zhigeng Pan, Zhengwei Zhang, Chenghua Fang, Shengquan Wang Jan 2019

Research On Augmented Reality Method Based On Unmarked Recognition, Li Qian, Shangbing Gao, Zhigeng Pan, Zhengwei Zhang, Chenghua Fang, Shengquan Wang

Journal of System Simulation

Abstract: As a kind of technology of superposing the virtual objects upon reality scene, AR (Augment Reality) expands the information quantity of the actual scene by virtual information. Aiming at the deficiency of previous AR application methods, the AR application method of unmarked recognition based on the optimized filtering was proposed in this paper. In this algorithm, filtering was used for image preprocessing to solve the poor matching efficiency problems of the past recognition algorithms, then three-dimensional model was established in two-dimensional images and the model was rendered in the two-dimensional plane. The experimental results show that, compared with …


Application Of Virtual Trial Makeup Based On Video, Jiayuan Liu, Jinfang Li, Hanwu He Jan 2019

Application Of Virtual Trial Makeup Based On Video, Jiayuan Liu, Jinfang Li, Hanwu He

Journal of System Simulation

Abstract: To try different cosmetic products in a convenient and low cost way, a virtual make-up algorithm based on a plane mesh model is proposed. The feature points are extracted from the face in the video by the Harr cascade classifier and the Dlib library. A mask pattern is built on the different parts of the face dynamically according to the texture coordinates of the plane mesh model. Theory is used to control the display area of the main texture of the planar mesh model. The mapping relationship between the main texture and the feature point coordinates of the planar …