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Articles 1 - 7 of 7
Full-Text Articles in Physical Sciences and Mathematics
Study On Hand Gesture Recognition And Portfolio Optimization Model Based On Svm, Zhiwei Cai, Shuyan Wu, Junfeng Song
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
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
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
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
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
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
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 …