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2010 International Conference on Intelligent Computation Technology and Automation, ICICTA 2010

作者： Yu, Jinxia Tang, Yongli Liu, Wenjing College of Computer Science and Technology Henan Polytechnic University Jiaozuo 454003 China Jiangsu Provincial Key Lab of Image Processing and Image Communication Nanjing University of Posts and Communication Nanjing 210003 China Department of Computer Science and Technology Tsinghua University Beijing 100084 China

ISBN: (纸本)9780769540771

It is very important to find diversity measure when to perform a resampling step in particle filter. By analyzing the inherent deficiency in resampling algorithm of particle filter, some diversity measures including effective sample size, population diversity factor and particle swarm diversity measure are introduced. Then combined with the simulation program using matlab 7.0 to track a single target motion from a fixed visual observation points, the performance of diversity measures in resampling algorithm of PF are evaluated. © 2010 IEEE.

关键词： Monte Carlo methods

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Adaptive resampling in particle filter based on diversity measures

Adaptive resampling in particle filter based on diversity me...

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International Conference on Computer Science and Education

作者： Yu, Jin-Xia Liu, Wen-Jing Tang, Yong-Li College of Computer Science and Technology Henan Polytechnic University Jiaozuo 454003 China Jiangsu Provincial Key Lab. of Image Processing and Image Communication Nanjing University of Posts and Communication Nanjing 210003 China Department of Computer Science and Technology Tsinghua University Beijing 100084 China

ISBN: (纸本)9781424460052

It is very important to find a criterion when to perform a resampling step. Aimed at this problem, an adaptive resampling algorithm in particle filter based on diversity measures is presented. Based on the analysis and comparison of two diversity measures that are effective sample size (ESS) and population diversity factor(PDF), the resampling algorithm based on ESS is introduced. On the basis of that, PDF is used for adaptively tuning the resampling threshold. At last, with the simulation program using matlab 7.0 to track a single target motion from a fixed visual observation points, the performance of the proposed algorithm is evaluated and its validity is verified. ©2010 IEEE.

关键词： MATlab

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Extraction method of microscopic moving particle basing on multimodal background model

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ICIC Express Letters, Part B: Applications 2015年第12期6卷 3153-3158页

作者： Zhang, Yanbin Yang, Zhangzhen Zhang, Hui Qin, Lei Image Processing and Image Communication Lab Jiangsu Key Lab of Wireless Communications Nanjing University of Posts and Telecommunications No. 66 New Mofan Road Nanjing210003 China Jiangsu Key Lab of Wireless Communications Nanjing University of Posts and Telecommunications No. 66 New Mofan Road Nanjing210003 China

Target extraction is a key technology for image measurement of moving particles distributed in fluidic system. In this paper, we propose a novel moving particle extraction method based on multimodal characteristic of the image. For the proposed particle extraction method, we firstly analyze the origin of multimodal characteristic of image background in the microscopic observation system, and then we design multimodal background model for particle extraction. For improving the performance of the model, we exploit the moving principle in the micro channel, and discuss the setting of learning rate. The experimental results demonstrate that the proposed methods achieve good performance compared with several traditional methods. © 2015, ICIC Express Letters Office. All rights reserved.

关键词： Extraction

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Mean Shift Object Tracking with Modified LTP

Mean Shift Object Tracking with Modified LTP

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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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Visibility Graph Analysis on EEG Signal

Visibility Graph Analysis on EEG Signal

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International Congress on image and Signal processing, BioMedical Engineering and Informatics

作者： Hongda Ji Tian Xu Wei Wu Jun Wang Image Processing and Image Communications Key Lab Nanjing University of Posts & Telecomm School of Public Health Southeast Univ.

ISBN: (纸本)9781509037117

We use the visibility graph analysis to research EEG signal and construct the complex network of EEG signal. In the paper, we construct the network by using EEG signal of the people with occupational stress and the normal people. Some properties of the complex network are found in this paper. The results of our experiment show that the properties of the normal people and the people with occupational stress are different.

关键词： EEG visibility graph occupational stress

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Video smoke removal based on low-rank tensor completion via spatial-temporal continuity constraint

Video smoke removal based on low-rank tensor completion via ...

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作者： Zhu, Hu Xu, Guoxia Liu, Lu Deng, Lizhen Jiangsu Province Key Lab on Image Processing and Image Communication Nanjing University of Posts and Telecommunication Nanjing China Department of Computer Science Norwegian University of Science and Technology Gjovik Norway National Engineering Research Center of Communication and Network Technology Nanjing University of Posts and Telecommunication Nanjing China

Smoke has a very bad effect on the outdoor vision system. Not only are the videos with poor visual effects obtained, but also the quality and structure of the videos are reduced. In this paper, we propose a video smoke removal method based on low-rank tensor completion via spatial-temporal continuity constraint. The proposed method is based on the smoke mixing model and consider the sparseness of smoke and the global and local consistency of clean video. Then, the optimal solution of the smoke removal algorithm model is quickly realized by the Alternating Direction Method of Multiplier. Finally, we evaluate the experiment results of real-world data and simulated data from the visual effects and objective indicators. And the experiment results show that our proposed algorithm can achieve better smoke removal results. © 2021 John Wiley & Sons, Ltd.

关键词： Smoke

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Scale adaptive block target tracking based on multi-layer convolution features and Kernel correlation filter

Scale adaptive block target tracking based on multi-layer co...

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2020 International Symposium on Automation, Information and Computing, ISAIC 2020

作者： Zhang, Ting Hu, Dong Zhang, Jing Jiangsu Province’s Key Lab of Image Procession and Image Communications Nanjing210003 China Education Ministry’s Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing210003 China Education Ministry’s Engineering Research Center of Ubiquitous Network and Heath Service Nanjing University of Posts and Telecommunications Nanjing210003 China

Target tracking is currently a hot research topic in Computer Vision and has a wide range of use in many research fields. However, due to factors such as occlusion, fast motion, blur and scale variation, tracking method still needs to be deeply studied. In this paper, we propose a block target tracking method based on multi-convolutional layer features and Kernel correlation filter. Our method divides the tracking process into two parts: target position estimation and target scale estimation. First, we block the target frame based on the condition number. Second, we extract the features by the convolutional layer and apply it to the kernel correlation filter to get the center position of different block targets. With the reliability of different blocks measured by the Barker coefficient, the overall target position center is obtained. Then, the affine transformation is adopted to achieve the scale adaptation. The algorithm in this paper is evaluated by the public video sequences in OTB-2013. Numerous experimental results demonstrate that the proposed tracking method can achieve target scale adaptation and effectively improve the tracking accuracy. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Target tracking

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Joint DBF and SAO parallel filtering based on multithread load balancing

Joint DBF and SAO parallel filtering based on multithread lo...

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2020 International Symposium on Automation, Information and Computing, ISAIC 2020

作者： Ma, Hao Hu, Dong Li, Yi Jiangsu Province’s Key Lab of Image Procession and Image Communications Nanjing210003 China Education Ministry’s Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing210003 China Education Ministry’s Engineering Research Center of Ubiquitous Network and Heath Service Nanjing University of Posts and Telecommunications Nanjing210003 China

This paper presents a joint parallel loop filtering algorithm based on multi-thread load balancing in HEVC decoding, which implements the parallel processing of deblocking filtering (DBF) and sample adaptive compensation (SAO). Because of the diversity of video, the texture of different regions in an image is also different, which leads to various CTU partition methods. Therefore, the number of the boundary to be filtered is greatly different, resulting the computation load among multiple threads unbalanced in parallel processing. To solve this problem, an area division scheme is proposed, which divides the image into multiple areas, and the number of boundaries to be filtered in each area is similar. Then, the mapping relationship table is used to allocate these areas to multiple threads for parallel processing, so as to achieve the load balancing among the filtering threads. Finally, the cache technology is used to combine DBF and SAO to reduce the delay between them and improve the overall parallelism of the loop filter. Experimental results show that the performance of the proposed load balancing joint filtering algorithm is 8.15% higher than the previous scheme. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Textures

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An improved image dehazing algorithm based on dark channel prior

An improved image dehazing algorithm based on dark channel p...

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IEEE Workshop on Advanced Research and Technology in Industry Applications (WARTIA)

作者： Jiajie Liu Jieying Zheng Ziguan Cui Guijin Tang Feng Liu Jiangsu Province Key Lab on Image Processing & Image Communications Nanjing University of Posts and Telecommunications Nanjing China Ministry of Education Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781479969906

image dehazing algorithm based on dark channel prior has been proved to be effective, but it cannot still guarantee accurate transmission. To solve this problem, we firstly propose a more reasonable estimation of atmospheric light, because bias in the atmospheric light estimation will cause an inaccurate transmission. Secondly, we improve the estimation of transmission in bright area so as to alleviate color distortion. After image recovery, we carry out denoising to improve the image quality. Finally, we use a blind image quality assessment method based on property of Human Visual System, and the experimental results show that this improved algorithm is more effective.

关键词： Mathematical model Equations image color analysis Atmospheric modeling Estimation image quality Noise reduction

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Wavelet permutation entropy analysis of Ventricular Fibrillation and Sudden Cardiac Death ECG signals

Wavelet permutation entropy analysis of Ventricular Fibrilla...

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2015 International Industrial Informatics and Computer Engineering Conference(IIICEC 2015)

作者： Lei Yang Fengzhen Hou Jun Wang Image Processing and Image Communications Key Lab. Nanjing Univ.of Posts & Telecomm School of Science China Pharmaceutical University

In this paper,we applied wavelet permutation entropy to analyze the Ventricular Fibrillation(VF) signals and Sudden Cardiac Death(SCD) signals for making an effective distinction from normal sinus rhythm(NSR) ***,three different ECG signals are decomposed by wavelet and reconstructed in each single *** highly discriminated frequency band will be chosen as our target ***,under the circumstances of different series length,embedding dimension and delay time,the main work is to distinguish the three ECG signals in different frequency bands based on the permutation entropy(PE).The results show that permutation entropy method can make a distinction between normal and abnormal ECG signals which aren't decomposed,but the effect of decomposing with wavelets is better *** the highest discriminated frequency band is from 15.625 Hz to 31.25 *** the point of different data length,embedding dimension and delay time,it was found that permutation entropy method have different effects and the findings may assist cardiac clinical diagnosis.

关键词： Ventricular Fibrillation Signals Sudden Cardiac Death Signals Wavelet Analysis Reconstruction Permutation Entropy

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