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

作者： Jiao Wang Changhong Chen Xiuchang Zhu Jiangsu Provincial Key Lab of Image Processing and Image Communication Nanjing University of Posts and Telecommunications

ISBN: (纸本)9781467321969

Action recognition is an important topic in computer vision and most current work focuses on view-dependent representations. In this paper, we develop a novel free viewpoint action recognition based on Self-similarity matrix (SSM), which tends to be stable across views. We choose Local Self-similarity (LSS) descriptor as our low-level feature, then SSM is calculated by computing the similarity between any pair of frame features. Each video sequence is represented using a diagonal descriptor vector extracted from the SSM. Support Vector Machines (SVM) is employed for classification. The encouraging experimental results on the public IXMAS multi-view data set demonstrate effectiveness of the proposed method.

关键词： local self-similarity descriptor self-similarity matrix diagonal feature action recognition view independent

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Multi-agent middleware for the integration of mobile supply chain

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Journal of Computers 2011年第7期6卷 1469-1476页

作者： Zhao, Weidong Wu, Haifeng Dai, Weihui Li, Xuan Yu, Fei Xu, Chen School of Software Fudan University Shanghai China Jiangsu Provincial Key Lab of Image Processing and Image Communications Nanjing University of Posts and Telecommunications Nanjing China

With the development of mobile network and communication technology, traditional supply chain management is gradually updating to mobile supply chain management, and multi-agent technology has been considered as a very efficient method for supply chain management in mobile environment. After considering the characteristics and limitations of mobile supply chain, and according to the requirements in the manufacturing domain, this paper designs a multi-agent middleware for mobile supply chain management, aiming to solve integration problems and shield off network and terminal heterogeneity in mobile environment, which can achieve mobile supply chain dynamic integration and then improve the efficiency of supply chain management. Its feasibility and efficiency was demonstrated by experiments. © 2011 ACADEMY PUBLISHER.

关键词： Middleware

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An improving MFCC features extraction based on FastICA algorithm plus RASTA filtering

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Journal of Computers 2011年第7期6卷 1477-1484页

作者： Zhao, Huan Hu, Lian Peng, Xiujuan Wang, Gangjin Yu, Fei Xu, Cheng School of Information Science and Engineering Hunan University Changsha China Jiangsu Provincial Key Lab of Image Processing and Image Communications Nanjing University of Posts and Telecommunications Nanjing China

FastICA is a kind of independent component analysis (ICA), which is robust and high performance algorithm, it can strongly remove signal correlation and ensure each signal to be independence. Through perceptual test, improving that RASTA is an idea which can denoise effectively. First, we remove signal correlation through FastICA algorithm, then we use RASTA filter to filtering the ceptral coefficients. Finally, we reduce dimension of the cepstral coefficients by the variances of cepstral coefficients in different dimension and obtain our features. By the HTK3.3, the speech feature extraction which was presented in this paper show the better robust in recognition experiment. © 2011 ACADEMY PUBLISHER.

关键词： Feature extraction

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An improved speech enhancement method based on teager energy operator and perceptual wavelet packet decomposition

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Journal of Multimedia 2011年第3期6卷 308-315页

作者： Zhao, Huan Peng, Xiujuan Hu, Lian Wang, Gangjin Yu, Fei Xu, Chen School of Information Science and Engineering Hunan University Changsha China Jiangsu Provincial Key Lab of Image Processing and Image Communications Nanjing University of Posts and Telecommunications Nanjing China

According to the distribution characteristic of noise and clean speech signal in the frequency domain, a new speech enhancement method based on teager energy operator (TEO) and perceptual wavelet packet decomposition (PWPD) is proposed. Firstly, a modified Mask construction method is made to protect the acoustic cues at the low frequencies. Then a level-dependent parameter is introduced to further adjust the thresholds in light of the noise distribution feature. At last the sub-bands which have very little influence are set directly 0 to improve the signal-to-noise ratio (SNR) and reduce the computation load. Simulation results show that, under different kinds of noise environments, this new method not only enhances the signal-to-noise ratio (SNR) and perceptual evaluation of speech quality (PESQ), but also reduces the computation load, which is very advantageous for real-time realizing. © 2011 ACADEMY PUBLISHER.

关键词： Signal to noise ratio

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Stereo Matching based on Robust Likelihoods and MST Leveraged Smoothness Priors

Stereo Matching based on Robust Likelihoods and MST Leverage...

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

作者： Tianliang Liu Liang Wang Xiuchang Zhu Jiangsu Provincial Key Lab of Image Processing and Image Communication College of Telecommunications and Information Engineering Nanjing University of Posts and Telecommunications

ISBN: (纸本)9781467321969

This paper proposes a global stereo correspondence using robust matching likelihoods and minimum spanning tree （MST） leveraged smooth priors in a probabilistic graphical model framework. The matching likelihoods of the stereo correspondence can be robustly constructed as data term by aggregating initial matching costs from Weber local descriptors using an unsymmetrical guided filtering in a linear model. The disparity priors are devised as smooth term to characterize the smoothness constraints leveraged by the MST structure. The presented stereo approach provides an effective and efficient way to reflect robust visual dissimilarity and resolve local and regional discontinuities. Experiments demonstrate that the proposed global stereo matching method can produce piecewise smooth, accurate and dense disparity map, while removing effectively the visual ambiguity of the stereo matching problem.

关键词： stereo vision Markov random field Weber descriptor minimun spanning tree QPBO optimization

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Flicker-Free Adaptive Enhancement for Infrared Video 13

Flicker-Free Adaptive Enhancement for Infrared Video

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13th International Conference on Wireless Communications and Signal processing, WCSP 2021

作者： Wei, Caixia Gan, Zongliang Nanjing University of Posts and Telecommunications Jiangsu Provincial Key Lab of Image Processing and Image Communication Nanjing China

ISBN: (纸本)9781665407854

Infrared videos often suffer from low contrast and insufficient texture. In order to improve poor visual effect, a novel infrared video enhancement method is proposed, which contains intra-frame brightness enhancement and inter-frame brightness continuity adjustment. In intra-frame brightness enhancement, it has two steps including global contrast enhancement and local details enhancement. To global contrast enhancement, the processed image contrast by geometric distribution, and it is incorporated into an optimization problem with a sorted histogram of each frame to yield a modified histogram. To local details enhancement, after Retinex decomposition, the reflection component is magnified by boundary preserving filter, and this strategy can effectively suppress noise in relatively uniform regions. Furthermore, to maintain inter-frame brightness continuity, adaptive parameters are introduced through optical flow to control the combination ratio of geometric distribution histogram, in which the enhancement degree of each frame can be adjusted according to inter-frame similarity and the moving region are enhanced adaptively according to the change of each frame. Experimental results demonstrate that proposed algorithm can effectively enhance the contrast and detail of infrared video, and improve the visual effect in subjective and objective quality evaluation. © 2021 IEEE.

关键词： Luminance

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A new super-resolution reconstruction method combining narrow quantization constraint set and motion estimation for H.264 compressed video

A new super-resolution reconstruction method combining narro...

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International Conference on image and Graphics

作者： Hu, Dong Zhao, Yingxue Xiao, Peng Jiangsu Provincial Key Lab of Image Processing and Image Communications Nanjing University of Posts and Telecommunications Nanjing 210003 China

ISBN: (纸本)9780769545417

Super-resolution (SR) reconstruction technique is mainly a task of reconstructing high resolution images from a sequence of low resolution images. The super-resolution technique for H.264 compressed video has been focused by many researchers recently. This paper briefly analyzes the narrow quantization constraint set method (NQCS), and then, in consideration of motion characteristic information of H.264 compressed video, proposes a new SR reconstruction method which combines NQCS with motion characteristic information, which are spatial domain motion estimation and frequency domain motion noise respectively. Experimental results of different standard test sequences compressed by H.264 are given. The simulation shows that both the NQCS+Mnoise method which combines NQCS with frequency domain motion noise, and the NQCS+M method which combines NQCS with spatial domain motion estimation, can get higher PNSR value than NQCS. Moreover, the NQCS+M method has better performance than NQCS+Mnoise method, and our proposed method is suitable for the SR reconstruction of H.264 compressed video. © 2011 IEEE.

关键词： Motion estimation

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Edge directed single image super resolution through the learning based gradient regression estimation 8th

Edge directed single image super resolution through the lear...

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8th International Conference on image and Graphics, ICIG 2015

作者： Si, Dandan Hu, Yuanyuan Gan, Zongliang Cui, Ziguan Liu, Feng Jiangsu Provincial Key Lab of Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing210003 China

ISBN: (纸本)9783319219622

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 based gradient estimation. In proposed method, the gradient of HR image is estimated by using the example based ridge regression model. 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. Moreover, the precomputed projective matrix of the ridge regression can reduce the computational complexity further. Experimental results suggest that the proposed method can achieve better gradient estimation of HR image and competitive SR quality compared with other SR methods. © Springer International Publishing Switzerland 2015.

关键词： Optical resolving power

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A novel improved binarized normed gradients based objectness measure through the multi-feature learning 8th

A novel improved binarized normed gradients based objectness...

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8th International Conference on image and Graphics, ICIG 2015

作者： Zhao, Danfeng Hu, Yuanyuan Gan, Zongliang Chen, Changhong Liu, Feng Jiangsu Provincial Key Lab of Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing210003 China

ISBN: (纸本)9783319219776

In this paper, we propose a novel improved binarized normed gradients (BING) objectness method based on the multi-feature boosting learning. A series of difference of gaussians (DoG) of the images with given parameters are used for the feature extraction stage, since the image DoG filter can better describe objects border. In addition, in training phase, the classifier can adaptively combine the features from different scales and different frequency components. Moreover, since the norm of the feature gradients is a simple 64D feature in the proposed framework, the computational complexity of the algorithm is in the same level compared with the BING measure. Experiments on the challenging PASCAL VOC 07 dataset show that the proposed method can not only achieve higher detection rate and average score than some current related objectness measures, but also lead to a very competitive accuracy of locating objects, even in some difficult cases. © Springer International Publishing Switzerland 2015.

关键词： Computational complexity

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Improvement of virtual view rendering based on depth image

Improvement of virtual view rendering based on depth image

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International Conference on image and Graphics

作者： Hu, Dong Sun, Jianfei Xu, Ping Jiangsu Provincial Key Lab of Image Processing and Image Communications Nanjing University of Post and Telecommunications Nanjing 210003 China

ISBN: (纸本)9780769545417

Virtual view rendering has great importance in 3-D display. In order to get high-quality image of an arbitrary view from 2-D source image, improvement on depth-image based rendering (DIBR) is studied in this paper. By analyzing the process of virtual view rendering of DIBR, an improved method is proposed, which generates new view by modifying parallax of two views and incorporating image inpainting. The parallax is deduced from depth information, and modified afterwards according to parallax gradient, so as to reduce hole regions before generating new view by 3-D image warping. To further remove the remaining holes, image inpainting combining texture and depth information is incorporated. Experimental results show the superiority of the proposed method. © 2011 IEEE.

关键词： image enhancement

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