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2012 IEEE 11th International Conference on Signal processing(ICSP 2012)

作者： ZHANG Shaona HU Dong HU Yanting Education Ministry's Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications The key lab of image processing and transmission of Jiangsu province Nanjing University of Posts and Telecommunications School of Telecommunication and Information Engineering Nanjing University of Posts and Telecommunications

ISBN: (纸本)9781467321969

A new scheme of object tracking with mean shift is put forward in this paper. At first, texture feature is fused in the processing by Local Ternary Pattern (LTP). Since LTP is sensitive to local noise, least median of squares (LMedS) algorithm is used to adaptively calculate the noise threshold for accurate estimation of the LTP texture information. Furthermore, target scale and orientation is estimated in case of partial occlusion or rotation, so as to realize robust object tracking. Experimental results show that the proposed algorithm can acquire robust tracking performance under complex background .

关键词： Object tracking, Mean Shift, LTP, LMedS

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Data model driven architecture (DMDA)

Data model driven architecture (DMDA)

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4th International Workshop on Advanced Computational Intelligence, IWACI 2011

作者： Chen, Chen Chen, Xueguang Liu, Hong Institute of Systems Engineering Huazhong University of Science and Technology Wuhan 430074 China Key Lab. for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781612843735

Based on the current development of Model Driven Architecture (MDA) in Enterprise Information System (EIS), the paper proposes a DMDA, a new development architecture to improve EIS development speed and quality. The basic idea of the DMDA is to take advantage of formal description, decomposition and re-use on EIS development process to let computer understand development demands of developers and then consequently generate some business models having nothing to do with specific technical realization, combine with specific technical basic platform to finally generate the EIS meeting actual demands based on data model. The practice proves the architecture is capable of simplifying EIS development difficulty, expediting application and development speed, improve development quality and achieve the rapid development purpose. © 2011 IEEE.

关键词： Software design

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Talking Detection in Collaborative Learning Environments 19th

Talking Detection in Collaborative Learning Environments

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19th International Conference on Computer Analysis of images and Patterns, CAIP 2021

作者： Shi, Wenjing Pattichis, Marios S. Celedón-Pattichis, Sylvia LópezLeiva, Carlos Image and Video Processing and Communications Lab Department of Electrical and Computer Engineering University of New Mexico AlbuquerqueNM United States Departtment of Language Literacy and Sociocultural Studies University of New Mexico AlbuquerqueNM United States

ISBN: (纸本)9783030891305

We study the problem of detecting talking activities in collaborative learning videos. Our approach uses head detection and projections of the log-magnitude of optical flow vectors to reduce the problem to a simple classification of small projection images without the need for training complex, 3-D activity classification systems. The small projection images are then easily classified using a simple majority vote of standard classifiers. For talking detection, our proposed approach is shown to significantly outperform single activity systems. We have an overall accuracy of 59% compared to 42% for Temporal Segment Network (TSN) and 45% for Convolutional 3D (C3D). In addition, our method is able to detect multiple talking instances from multiple speakers, while also detecting the speakers themselves. © 2021, Springer Nature Switzerland AG.

关键词： Computer aided instruction

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A probability-based object tracking method

A probability-based object tracking method

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4th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2013

作者： Song, Xu Li, Guoqiang Li, Ying Zhang, Yanning Shaanxi Province Key Lab. of Speech and Image Information Processing Northwestern Polytechnical University Xi'an 710129 China Science and Technology on Electro-optic Control Laboratory Louyang 471009 China

ISBN: (纸本)9783642420566

Here we take advantage of the signal recovery power of Compressive Sensing (CS) to significantly reduce the computational complexity brought by the high-dimension image data, then an effective and efficient low-dimensional subspace representation of the object is computing by applying Principal Component Analysis (PCA) to a collection of object observations which are low-dimensional vectors derived from CS. An incremental PCA algorithm is used to update this subspace model for characterizing the object appearance changes. Meanwhile, two distances derived from Probabilistic Principal Component Analysis (PPCA): distance from feature space (DFFS) and distance in feature space (DIFS), are used to describe visual similarity between the learned subspace representation model and candidate targets. Comparing with the traditional used reconstruction error, the sum of two distances: DFFS + DIFS, is more accurate and more robust to noises and partial occlusions. Numerous experiment demonstrate that subspace representation model can handle the situation that target objects experience pose changes, scale changes, significant illumination variation, partial occlusions and so on. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Compressed sensing

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Epidemic spreading with variant infection rates on scale-free network

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6th International Symposium on Neural Networks, ISNN 2009

作者： Hong, Liu Ouyang, Min Mao, Zijun Chen, Xueguang Institute of System Engineering Huazhong University of Science and Technology Wuhan 430074 China Key Lab. for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)3642015123

In this paper, we proposed a susceptible-infected model with variant infection rates because different individuals have different resistance to diseases in different periods of real epidemic events. We consider two cases: Case 1, we know every individual's infection rate to a kind of epidemic, satisfy a type of distribution. Case 2, assume all individuals have same initial infection rates, a susceptible individual's infection rate will be less than the initial rate if he is not infected after limited number of contacts with infected ones. For both two cases, at the time tD, preventive and control measures bring into effects, every individual's infection rate would decrease. We implemented this models on scale-free networks, and found that the epidemic process before the time tD in Case 1 is almost the same as that in Standard SI model if the infection rate in Standard SI model equals the mean infection rate in Case 1. Furthermore, using numerical simulation, we analysis the effects of the parameter tD, and find the bimodal distribution of final infection rates. Finally, we conclude what we get in this paper and give our future direction. © 2009 Springer Berlin Heidelberg.

关键词： Complex networks

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Hydrodynamics-Informed Neural Network for Simulating Dense Crowd Motion Patterns 24

Hydrodynamics-Informed Neural Network for Simulating Dense C...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Zhou, Yanshan Lai, Pingrui Yu, Jiaqi Xiong, Yingjie Yang, Hua Institute of Image Communication and Network Engineering Shanghai Jiao Tong University Shanghai China Shanghai Key Lab of Digital Media Processing and Transmission Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9798400706868

With global occurrences of crowd crushes and stampedes, dense crowd simulation has been drawing great attention. In this research, our goal is to simulate dense crowd motions under six classic motion patterns, more specifically, to generate subsequent motions of dense crowds from the given initial states. Since dense crowds share similarities with fluids, such as continuity and fluidity, one common approach for dense crowd simulation is to construct hydrodynamics-based models, which consider dense crowds as fluids, guide crowd motions with Navier-Stokes equations, and conduct dense crowd simulation by solving governing equations. Despite the proposal of these models, dense crowd simulation faces multiple challenges, including the difficulty of directly solving Navier-Stokes equations due to their nonlinear nature, the ignorance of distinctive crowd characteristics which fluids lack, and the gaps in the evaluation and validation of crowd simulation models. To address the above challenges, we build a hydrodynamic model, which captures the crowd physical properties (continuity, fluidity, etc.) with Navier-Stokes equations and reflects the crowd social properties (sociality, personality, etc.) with operators that describe crowd interactions and crowd-environment interactions. To tackle the computational problem, we propose to solve the governing equation based on Navier-Stokes equations using neural networks, and introduce the Hydrodynamics-Informed Neural Network (HINN) which preserves the structure of the governing equation in its network architecture. To facilitate the evaluation, we construct a new dense crowd motion video dataset called Dense Crowd Flow Dataset (DCFD), containing six classic motion patterns (line, curve, circle, cross, cluster and scatter) and 457 video clips, which can serve as the groundtruths for various objective metrics. Numerous experiments are conducted using HINN to simulate dense crowd motions under six motion patterns with video clips fro

关键词： Navier Stokes equations

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Analysis of alpha rhythm epileptic Electroencephalogram based on Inner composition alignment

Analysis of alpha rhythm epileptic Electroencephalogram base...

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2016 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics(AMEII 2016)

作者： Yiyi He Danqin Xing Jiaqin Wang Jia-Fei Dai Jun Wang Feng-Zhen Hou Image Processing and Image Communications Key Lab Nanjing Univ.of Posts & Telecomm. Nanjing General Hospital of Nanjing Military Command School of Science China Pharmaceutical University

ISBN: (纸本)9781510823808

The EEG signal is an important tool for the diagnosis and prediction of epilepsy due to EEG containing a large number of physiological and pathological *** on alpha rhythm multi-channel EEG(electroencephalogram),this paper applied inner composition alignment(IOTA) algorithm to construct brain functional network and visualize the network *** is to apply the algorithm to calculate and analyze IOTA coefficient,the node average degree and clustering coefficient of epileptic brain network for studying if epileptic brain network is significantly different from those of *** results show that IOTA coefficient of epileptic brain network obviously differs from the normal by calculating T testing with SPSS software,which proved that the effectiveness of the algorithm to distinguish IOTA coefficient of epileptic brain network.

关键词： alpha rhythm Electroencephalogram epileptic Inner composition alignment

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A NOVEL CROSS-LAYER STRATEGY OF VIDEO TRANSMISSION TO SOLVE PERFORMANCE ANOMALY IN MULTI-RATE IEEE 802.11 NETWORKS

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Journal of Electronics(China) 2011年第3期28卷 349-358页

作者： Tang Guijin Zhu Xiuchang Key Lab of Image Processing ＆ Communication Nanjing University of Posts and Telecommunications Nanjing 210003 China

When wireless hosts use different rates to transmit data in IEEE 802.11 networks, it will take on the state of performance anomaly which will severely decrease the throughputs of all the higher rate hosts. Hence, it is bad for video service transmission. Considering that video is very sensitive to packet delivery delay but can tolerate some packet losses, we propose a novel cross-layer scheme which takes these two characteristics into consideration. Firstly, the maximum number of retransmissions for a video Medium Access Control (MAC) frame is computed in MAC layer according to video frame rate requirement of application layer and current access delay of MAC layer. Secondly, within the margin of the tolerant Packet Loss Rate (PLR) of application layer, several video MAC frames are allowed to drop so that we can adaptively select the transmission rate as high as possible for the rest of video MAC frames in terms of current channel quality and the maximum number of retransmissions. Experiment results show that the proposed method can reduce the delay and jitter of video service and improve the throughputs of fast hosts. Therefore, it increases the quality of reconstructed video to a certain extent and relieves the performance anomaly of network effectively.

关键词： Multi-rate Video transmission IEEE 802.11 Performance anomaly Cross-layer

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The complexity of occupational stress electroencephalogram

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Occupational Diseases and Environmental Medicine 2013年第1期1卷 1-3页

作者： Honger Tian Lili Cao Jun Wang Tian Xu Yongguo Zhan Ling Liu Image Processing and Image Communications Key Lab College of Geo & Bio Information Nanjing University of Posts & Tele- comm Nanjing China Key Laboratory of Environment Medicine and Engineering Ministry of Education School of Public Health Southeast University Nanjing China

It is an important method for using electroencephalogram (EEG) to detect and diagnose occupational Stress in clinical practice. In this paper, the complexity analysis method based on Jensen-Shannon Divergence was used to calculate the complexity of occupational stress electroencephalogram from students and *** study found that the complexity of nurses’ EEG was higher than that of students’ EEG. The result can be used to assisted clinical diagnosis.

关键词： Occupational Stress Electroencephalogram Students Nurses Jensen-Shannon Divergence

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Interdependency analysis of infrastructures

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6th International Symposium on Neural Networks, ISNN 2009

作者： Mao, Zijun Hong, Liu Fei, Qi Ouyang, Ming Institute of System Engineering Huazhong University of Science and Technology Wuhan 430074 China Key Lab. for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)3642015123

Electric power, potable water, telecommunications, natural gas, and transportation are examples of critical infrastructures, the intrinsic feature of which are suitable for network analysis. This paper proposes a method framework based on the complex network to explore the interdependency of these infrastructures. We describe the topological characterization of two interdependent small-sized real networks, based on which the interdependent model is devised. We define the interdependent factor to characterize the direct interdependency of two infrastructures, and also its fluctuation in the situations of random removal and targeted removal on the electric and water infrastructures is studied. Furthermore we propose a matrix M to reflect all direct and indirect interactions among infrastructures, which also makes contributions to the understanding of infrastructures catastrophes. © 2009 Springer Berlin Heidelberg.

关键词： Complex networks

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