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IEEE International Symposium on Intelligent Signal processing and communication Systems (ISPACS)

作者： Han Shen Xiu-chang Zhu Jiangsu Province Key Lab on Image Processing & Image Communication Nanjing University of Posts and Telecommunications China

As no reference frame can be obtained in Intra-frame error concealment, reducing the degradation of spatial reconstructed image is one of the key techniques in error concealment. In this paper, a novel spatial error concealment algorithm based on fuzzy clustering for Intra-frame in H.264 is proposed. This proposed algorithm gives a new selection of eigenvectors and similarity measurement for fuzzy clustering. The experimental results show that the proposed algorithm can improve the edge details, achieve a better subjective quality of the recovered image and increase PSNR (Peak Signal-to-Noise Ratio) as well.

关键词： Clustering algorithms Signal processing algorithms image reconstruction Degradation PSNR Resilience Video sequences Frequency Discrete cosine transforms Fuzzy systems

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Fire surveillance method based on quaternionic wavelet features

Fire surveillance method based on quaternionic wavelet featu...

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16th International Multimedia Modeling Conference on Advances in Multimedia Modeling, MMM 2010

作者： Yu, Zhou Xu, Yi Yang, Xiaokang Institute of Image Communication and Information Processing Shanghai Jiaotong University Shanghai 200240 China Shanghai Key Lab of Digital Media Processing and Transmissions Shanghai 200240 China

ISBN: (纸本)3642113001

Color cues are important for recognizing flames in fire surveillance. Accordingly, the rational selection of color space should be considered as a nontrivial issue in classification of fire elements. In this paper, quantitative measures are established using learning-based classifiers to evaluate fire recognition accuracy within different color spaces. Rather than dealing with color channels separately, the color pixels are encoded as quaternions so as to be clustered as whole units in color spaces. Then, a set of quaternion Gabor wavelets are constructed to establish an comprehensive analysis tool for local spectral, spatial and temporal characteristics of fire regions. Their quaternion Gaussian kernels are used to represent the spectral distribution of fire pixel clusters. In addition, a 2D band-pass filter kernel contained in the quaternion Gabor extracts spatial contours of fire regions. Another 1D temporal filter kernel is enforced to capture random flickering behavior in the fire regions, greatly reducing the false alarms from the regular moving objects. For early alerts and high detection rate of fire events, smoke region is also recognized from its dynamic textures in the proposed fire surveillance system. Experimental results under a variety of conditions show the proposed vision-based surveillance method is capable of detecting flame and smoke reliably. © 2010 Springer-Verlag Berlin Heidelberg.

关键词： Fires

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Part-based human gait identification under clothing and carrying condition variations

Part-based human gait identification under clothing and carr...

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International Conference on Machine Learning and Cybernetics

作者： Li, Ning Xu, Yi Yang, Xiao-Kang Institute of Image Communication and Information Processing Shanghai JiaoTong University Shanghai 200240 China Shanghai Key Lab of Digital Media Processing and Transmissions Shanghai 200240 China

ISBN: (纸本)9781424465262

Gait recognition has already achieved satisfactory performance on small databases under ideal conditions. Most of the existing approaches represent gait pattern using a locomotion model or statistic model of human silhouette. However, it is still a challenging task to conduct human gait identification under variations of clothing and carrying condition in real scenes. In this paper, an adaptive part-based feature selection method is proposed to filter out interference feature blocks and a matching procedure is performed to identify the correct subject. Compared with the state-of-the-art methods on a large standard dataset, the proposed method shows an encouraging computational complexity reduction and performance improvement in identification rates. © 2010 IEEE.

关键词： Feature Selection

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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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Edge directed single image super resolution through the learning based gradient regression estimation

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ICIC Express Letters, Part B: Applications 2016年第2期7卷 337-344页

作者： Wang, Guogang Gan, Zongliang Zhu, Xiuchang Jiangsu Provincial Key Lab of Image Processing and Image Communication Nanjing University of Posts and Telecommunications No. 66 Xinmofan Road Nanjing China

Single image super resolution (SR) aims to estimate high resolution (HR) image from the low resolution (LR) one, and estimating accuracy of HR image gradient is very important for edge directed image SR methods. In this paper, we propose a novel edge directed image SR method by learning simple priors by mapping functions. Recognizing that the training samples of the given sub-set for regression should have similar local geometric structure based on clustering, we employ high frequency of LR image patches with removing the mean value to perform such clustering. Then we learn effective mapping functions of gradient of bicubic image patches and that of HR image patches for each cluster. Experimental results suggest that the proposed method can achieve better gradient estimation of HR image and competitive SR quality compared with other SR methods. © 2016 ICIC International.

关键词： Optical resolving power

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Object detection by clustering-based nonparametric kernel density estimation

Object detection by clustering-based nonparametric kernel de...

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作者： Hu, D. Hu, J. Education Ministry's Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications China Jiangsu Province's Key Lab of Image Procession and Image Communications Nanjing University of Posts and Telecommunications China

ISBN: (纸本)9781845648282

Nonparametric model is one of the popular ones for background modeling for its ability to adapt to changes quickly in dynamic environment and enable very sensitive detection of moving objects. However, the method is too complex and computationally inefficient to real-time application. In this paper, a fast and efficient scheme for moving object detection by nonparametric background modeling was proposed, whereas the background was modeled combining clustering theory to eliminate the large amount of redundant information and noise pixels in background modeling stage. Moreover, adaptive background and temporal differencing was used to filter out unchanged background pixels, thus enabling an additional reduction in computational requirements and improving the detection results. Besides, RGB color components were substituted by chromaticity coordinates to suppress shadow effects. Experimental results demonstrated the effectiveness of the proposed algorithm. © 2014 WIT Press.

关键词： Object detection

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Content-based image retrieval using fuzzy hamming distance

Content-based image retrieval using fuzzy hamming distance

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2007 8th International Conference on Electronic Measurement and Instruments, ICEMI

作者： Hu, Xuelong Yang, Li Zhang, Gensheng School of Information Engineering Yangzhou University Yangzhou 225009 China Jiangsu Province Key Lab. for Image Processing and Communication Nanjing University of Post and Telecommunications Nanjing 215006 China Jiangsu Province Key Lab. for Computer Information Processing Technology Suzhou University Suzhou 215006 China

ISBN: (纸本)1424411351

This paper addresses an effective issue of content-based image retrieval (CBIR) by presenting Fuzzy Hamming Distance (FHD). Firstly, the theory of FHD is introduced, which includes degree of difference and cardinality of the fuzzy set, and then follows defuzzification of FHD which is used as a fuzzy similarity measure. In the experiment, the image retrieval results show this method can be employed to capture implicitly some semantic contents of the image in addition to other features such as color, texture and shape. Finally, an implemented prototype system demonstrates a promising retrieval performance for a test database, as compared with FUZZYCLUB system. © 2007 IEEE.

关键词： Hamming distance

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A new method for semi-automatic image annotation

A new method for semi-automatic image annotation

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2007 8th International Conference on Electronic Measurement and Instruments, ICEMI

作者： Xuelong, Hu Yuhui, Zhang Li, Yang School of Information Engineering Yangzhou University Yangzhou 225009 China Jiangsu Province Key Lab. of Image Processing and Communication Nanjing University of Post and Telecommunications Nanjing 215006 China Jiangsu Province Key Lab. of Computer Information Processing Technology Suzhou University Suzhou 215006 China

ISBN: (纸本)1424411351

Semantic-based image retrieval bridges the gap between visual features and human understanding of image in the field of image retrieval. image annotation is one important technology of image retrieval based on the semantic. This paper proposed one method to realize semi-automatic image annotation with the tool Support Vector Machine (SVM). The image collection was divided into two parts, one for manual annotation and the other for testing. After being classified by SVM, the output was changed into a probability, and K-NN algorithm was applied to get the keywords for unlabeled images. The experiments show that the approach is feasible. © 2007 IEEE.

关键词： Support vector machines

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Research on moving object detection based on the Bayesian theory

Research on moving object detection based on the Bayesian th...

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作者： Hu, D. Liu, X. Education Ministry's Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications China Jiangsu Province's Key Lab of Image Procession and Image Communications Nanjing University of Posts and Telecommunications China

ISBN: (纸本)9781845648282

For effective and efficient detection of moving objects from complex surveillance scenarios, a novel integrated object detection scheme based on clustering and Bayesian theory is proposed in this paper. The algorithm conducts clustering analysis in the time domain as the pre-segmentation step for later Bayesian judgment processing. Furthermore, temporal differential image was used to classify dynamical and static pixels, which were then used to direct the Bayesian judgment with proper models. The clustering processing reduced the number of the mixture models, which in turn, reduced the computational complexity while ensuring accurate moving object detection. Simulation results show that the proposed scheme well exploited the temporal correlation of the video sequences and the accuracy of the detected objects can be improved by nearly 20% compared to the typical Gaussian mixture modeling algorithm. © 2014 WIT Press.

关键词： Object detection

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Network flow based collective behavior analysis

Network flow based collective behavior analysis

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2013 International Workshop on Behavior and Social Informatics and Computing, BSIC 2013

作者： Hu, Yuting Xie, Rong Zhang, Wenjun Institute of Image Communication and Network Engineering Shanghai Key Lab. of Digital Media Processing and Transmission Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9783319040479

With the large-scale activities increasing gradually, the intelligent video surveillance system becomes more and more popular and important. The trajectory identification and behavior analysis are very important techniques for the intelligent video surveillance system. This paper focuses on the trajectory identification and behavior analysis framework for video surveillance system. The framework is implemented on footbridge video and queuing video of Shanghai World Expo 2010 video surveillance system. The experimental results show the efficiency of our proposed framework. © Springer International Publishing Switzerland 2013.

关键词： Integer programming

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