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Laplacian coordinates-based motion transition for data-driven motion synthesis

IET Image Processing 2012年第9期6卷 1331-1337页

作者： Yi, P. Zhang, Q. Wei, X. School of Mechanical and Engineering Dalian University of Technology Dalian 116024 China Key Laboratory of Advanced Design and Intelligent Computing Dalian University Ministry of Education Dalian 116622 China

As a fundamental technique in data-driven (or example-based) methods, motion blending has been employed to produce new motion clip from two or more clips or introduced as a medium to improve the final result of other method, for example, motion graphs. As methods of motion blending always require the system or users to classify the motion samples, it is difficult to accomplish motion blending automatically and to preserve local details, such as angular accelerations of joints of original motions. In this study, the authors developed a framework based on Laplacian coordinates to produce transitions between two motion clips, emphasising on preserving local details, without any need of motion classification. At first, multidimensional Laplacian coordinates are introduced to present local details of joints' angle. Then an error function is deduced to measure how much result motions differ from original ones in local details. By minimising such error function, new motions can then finally generated, which can preserve local details of input motion clips as much as possible. The following experiments show the effectiveness of the authors' framework. © The Institution of Engineering and Technology 2012.

关键词： Laplace transforms

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The Temporal Structural Pattern in Scientific Collaborative Behavior from the Perspective of Complex Network 23rd

The Temporal Structural Pattern in Scientific Collaborative...

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23rd International Symposium on Knowledge and Systems Sciences, KSS 2024

作者： Zholdoshbaeva, Elina Zhang, Shuang Liu, Feifan Xia, Haoxiang Institute of Systems Engineering Dalian University of Technology No. 2 Linggong Road Liaoning Dalian116024 China Center for Big Data and Intelligent Decision-Making Dalian University of Technology Linggong Road Liaoning Dalian116024 China School of Business East China University of Science and Technology 130 Meilong Road Xuhui District Shanghai200237 China Institute for Advanced Intelligence Dalian University of Technology Linggong Road Liaoning Dalian116024 China Key Laboratory of Social Computing and Cognitive Intelligence Ministry of Education of China Linggong Road Liaoning Dalian116024 China

ISBN: (纸本)9789819601776

The rapid advancement of science has underscored the importance of collaboration among scientists. While many studies have explored the structure of collaboration networks, there is a lack of comprehensive quantitative research on the temporal patterns of these collaborations. This study addresses this gap by analyzing temporal scientific collaboration networks in physics, spanning from 1960 to 2021, using complex network theories and methods. By constructing five-year temporal collaborative networks and employing metrics such as network diameter, shortest path, and clustering coefficient, this research reveals an increase in connectivity and small-world characteristics over time. Additionally, community detection highlights a shift towards specialized collaboration patterns and increased cross-community interactions. The study also uncovers growing centrality and social stratification within the research system, with the "rich club" phenomenon indicating strong and dynamic collaborations among highly connected scientists. Temporal analysis shows that while ultra-high connectivity scientists engage in fluctuating relationships, medium-high connectivity scientists maintain more stable collaborations. These findings provide insights into the evolution of collaborative behaviors and inform science policy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Collaborative learning

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Digital image watermarking robust to geometric attacks based on Wavelet domain

Digital image watermarking robust to geometric attacks based...

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2010 IEEE 5th International Conference on Bio-Inspired computing: Theories and Applications, BIC-TA 2010

作者： Ma, Na Zhang, Qiang Li, Ying Key Laboratory of Advanced Design and Intelligent Computing Dalian university Ministry of Education Province Dalian 116622 China

ISBN: (纸本)9781424464388

This paper presents a new wavelet domain watermarking method, the carrier image using wavelet decomposition. After the Walsh transform low frequency wavelet coefficients, calculated by block adaptive embedding strength, modify the wavelet coefficients of each block, and then do singular value decomposition (SVD), repeat on embedded watermark in the singular value. Fractional part of the anti-transformed image is saved, correction of the watermarked image can be accurately extracted watermark. The experimental results demonstrate that the proposed algorithm can effectively resist cutting, scaling, translation and other geometric attacks, attacks in general are also robust. © 2010 IEEE.

关键词： Singular value decomposition

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3D Ear Shape Matching Using Joint -Entropy

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Journal of Computer Science & Technology 2015年第3期30卷 565-577页

作者：孙晓鹏李思慧韩枫魏小鹏 Institute of Computer Systems School of Computer and Information Technology Liaoning Normal University Dalian 116029 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications Beijing 100876 China School of Mechanical and Engineering Dalian University of Technology Dalian 116024 China Key Laboratory of Advanced Design and Intelligent Computing Dalian University Dalian 116622 China

In this article, we investigate the use of joint a-entropy for 3D ear matching by incorporating the local shape feature of 3D ears into the joint a-entropy. First, we extract a sut^cient number of key points from the 3D ear point cloud, and fit the neighborhood of each key point to a single-value quadric surface on product parameter regions. Second, we define the local shape feature vector of each key point as the sampling depth set on the parametric node of the quadric surface. Third, for every pair of gallery ear and probe ear, we construct the minimum spanning tree （MST） on their matched key points. Finally, we minimize the total edge weight of MST to estimate its joint a-entropy the smaller the entropy is, the more similar the ear pair is. We present several examples to demonstrate the advantages of our algorithm, including low time complexity, high recognition rate, and high robustness. To the best of our knowledge, it is the first time that, in computer graphics, the classical information theory of joint a-entropy is used to deal with 3D ear shape recognition.

关键词： joint a-entropy minimum spanning tree local shape feature ear matching ear recognition

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LMP-GAN: Out-Of-Distribution Detection For Non-Control Data Malware Attacks

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IEEE Transactions on Pattern Analysis and Machine Intelligence 2025年 PP卷 PP页

作者： Wood, David Kapp, David Kebede, Temesgen Hirakawa, Keigo Wuhan University School of Computer Science China Wuhan University National Engineering Research Center for Multimedia Software Hubei Key Laboratory of Multimedia and Network Communication Engineering China Zhongguancun Academy China Wuhan University State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing China Sun Yat-sen University School of Geography and Planning China Mohamed bin Zayed University of Artificial Intelligence United Arab Emirates Chongqing University College of Computer Science China The University of Tokyo Japan RIKEN Center for Advanced Intelligence Project Japan Intelligent Science & Technology Academy Limited CASIC China iFlytek Company Ltd. National Engineering Research Center of Speech and Language Information Processing China Nanyang Technological University College of Computing & Data Science Singapore Henan Academy of Sciences Aerospace Information Research Institute China

Anomaly detection is a common application of machine learning. Out-of-distribution (OOD) detection in particular is a semi-supervised anomaly detection technique where the detection method is trained only on the inlier (in-distribution) samples - unlike the fully supervised variant, the distribution of the outlier samples are never explicitly modeled in OOD detection tasks. In this work, we design a novel GAN-based OOD detection network specifically designed to protect a cyber-physical signal systems from novel Trojan malware called non-control data (NCD) attack that evades conventional malware detection techniques. Inspired in part by the classical locally most powerful (LMP) test in statistical inferences, the proposed LMP-GAN trains the OOD detector (discriminator) by generating OOD samples that are aimed at making maximal alteration to the inlier samples while evading detection. We experimentally compare the results to the state-of-the-art anomaly detection methods to demonstrate the benefits and the appropriateness of the LMP-GAN OOD detector. © 2025 IEEE.

关键词： Malware

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An Improved Correlation-Based Just-in-Time Modeling Method Using Dynamic Partial Least Squares and Adaptive Local Domain Partition 29

An Improved Correlation-Based Just-in-Time Modeling Method U...

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第29届中国控制与决策会议

作者： Xiaolong Chen Zhizhong Mao Runda Jia Dong Xiao Xiaojun Wang College of Information Science & Engineering Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Key Laboratory of Advanced Design and Intelligent Computing Dalian university

ISBN: (纸本)9781509046584

This paper proposes an improved correlation-based just-in-time modeling method,referring to as the ICo JIT,for improving the prediction accuracy and real-time performance of the conventional correlation-based just-in-time(CoJIT) modeling *** achieve this objective,a novel adaptive local domain partition method has been developed based on the moving window technique and the fitting precision,which takes into account the input and output information simultaneously and has potentially the capabilities of obtaining the optimal local domain partition adaptively and capturing new process states by adding new local *** dynamic partial least squares and adaptive local domain partition method,multiple local domains and corresponding local models can be obtained during the offline operation *** online computation burden is reduced compared to CoJIT modeling *** addition,the proposed ICoJIT modeling method can efficiently deal with nonlinearity and time-varying behavior of processes as well as the CoJIT modeling *** effectiveness of the proposed method is demonstrated through a real industrial process dataset in sulfur recovery unit process.

关键词： Soft sensor Correlation-based just-in-time modeling Partial least squares Local domain partition Moving window

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A Text Structure-based Extractive And Abstractive Summarization Method 7

A Text Structure-based Extractive And Abstractive Summarizat...

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7th International Conference on intelligent computing and Signal Processing, ICSP 2022

作者： Yan, Jing Zhou, Shihua Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian China

ISBN: (纸本)9781665478571

Extraction summarization and abstraction summarization have advantages and disadvantages, so how to better combine these two ways has become a difficult problem. To address this challenge, this paper proposed a new fusion method. The major novelty lies in the design of the new method. Wherein our approach, first, use the text structure information and the idea of the K-means algorithm to divide the text into regions, and then the main part and the non-main parts are determined according to the distribution of the subject words. Next, apply information extraction on the main part and text generation on the non-main parts. Finally, the two parts of the summarization are merged according to the sequence of the text. Experimental results show that the quality of the summarization is better than that of extraction summarization and abstraction summarization. In addition, to make the method more targeted in Chinese text processing, the Cw2vec model based on Chinese stroke information is used in the encoding process, and the experiment proves that the quality of summarization can be further improved. © 2022 IEEE.

关键词： Text processing

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SCFNet: A Spatial-Channel Features Network Based on Heterocentric Sample Loss for Visible-Infrared Person Re-identification 16th

SCFNet: A Spatial-Channel Features Network Based on Heteroc...

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16th Asian Conference on Computer Vision, ACCV 2022

作者： Su, Peng Liu, Rui Dong, Jing Yi, Pengfei Zhou, Dongsheng Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian University Dalian China

ISBN: (纸本)9783031262838

Cross-modality person re-identification between visible and infrared images has become a research hotspot in the image retrieval field due to its potential application scenarios. Existing research usually designs loss functions around samples or sample centers, mainly focusing on reducing cross-modality discrepancy and intra-modality variations. However, the sample-based loss function is susceptible to outliers, and the center-based loss function is not compact enough between features. To address the above issues, we propose a novel loss function called Heterocentric Sample Loss. It optimizes both the sample features and the center of the sample features in the batch. In addition, we also propose a network structure combining spatial and channel features and a random channel enhancement method, which improves feature discrimination and robustness to color changes. Finally, we conduct extensive experiments on the SYSU-MM01 and RegDB datasets to demonstrate the superiority of the proposed method. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Infrared imaging

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A Color Image Encryption Algorithm Based on Complementary Map and Iterative Convolutional Code 24

A Color Image Encryption Algorithm Based on Complementary Ma...

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8th International Conference on Machine Learning and Soft computing, ICMLSC 2024

作者： Xie, Yanlu Zhou, Shihua Lv, Hui Wang, Bin Che, Chao Zhang, Qiang Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian University Dalian China

ISBN: (纸本)9798400716546

Encryption is a valid means to safeguard the safety of images, and for color images, encryption should be performed considering the intrinsic correlation between R, G, and B components. In this paper, we propose an image encryption algorithm based on a complementary map and an iterative convolutional code. Firstly, the plain image is input into the convolutional encoders for iteration to generate the correctional secret key. Secondly, we design a new complementary map. From the test data, the new chaotic map has passed the NIST testing, exhibits a good chaotic characteristic, and has a wider range of chaotic parameters. Thirdly, global scrambling is performed on the color image to disrupt the distribution between R, G, and B. Then, a row-layer and a column-layer are randomly selected to form a set of elements to be encrypted. Finally, performing global diffusion on the image further increases the safety of our scheme. Experimental results show that our algorithm has a preferable encryption effect and elevated safety. © 2024 ACM.

关键词： Convolutional codes

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View-dependent fast real-time generating algorithm for large-scale terrain

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Procedia Earth and Planetary Science 2009年第1期1卷 1147-1151页

作者： Jin, Hai-liang Lu, Xiao-ping Liu, Hui-jie Key Laboratory of Mine Spatial Information Technologies State Bureau of Surveying and Mapping Henan Polytechnic University Jiaozuo 454000 China Key Laboratory of Advanced Design and Intelligent Computing Dalian University Dalian 116622 China

In order to eliminate the popping effect of switching among levels of detail and to increase the frame rates with high image quality during the fly-through of large-scale terrain, this paper put forward a new bottom-up modeling strategy, which constructed simplified terrain triangle mesh globally and updated mesh nodes dynamically. Employed hybrid culling technique based on blocks and triangle faces and simplified computing method for screen-space errors to select appropriate terrain nodes rapidly. Then updated the Delaunay terrain mesh by adding nodes, deleting nodes and modifying locally. At the same time achieved self-adaptive control for screen-space error tolerance during the terrain fly-through. Results of simulation experiments demonstrate that the algorithm eliminates popping effect effectively, and has a higher frame rate compared with other algorithms. So it is particularly suitable for close-distance fly-through simulation of large-scale terrain. © 2009.

关键词： Landforms Image quality Visualization Bottom up modeling computing methods Delaunay Error tolerance Frame rate High image quality Large scale terrain Levels of detail Mesh nodes Other algorithms Real time visualization Self adaptive control Simulation experiments Terrain meshes Triangle mesh View dependent

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