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2008 IEEE International Conference Neural Networks and Signal processing, ICNNSP

作者： Xuelong, Hu Yan, Tang Jun, Cai School of Information Engineering Yangzhou University Yangzhou Jiangsu 225009 China Jiangsu Province Key Lab. for Image Processing and Image Communication Nanjing University of Posts and Communications Nanjing Jiangsu 210003 China

ISBN: (纸本)9781424423118

Head-related Transfer Functions (HRTFs) refer to the spectral filtering from sound sources to listeners' eardrums or ear canals. As an effective model structure, the degree of the IIR filter approximation of the HRTFs, whose design and implementation is a specific spectrum function approximation process, is much lower than that of the FIR. Based on the assessment of HRTFs different importance for sound sources recognition in different spectrum bands, and associated with some perspectives of psychoacoustics in spatial hearing, adaptive and revalued coding genetic algorithm (GA) is applied to the approximation of the HRTFs zero-pole model. The results show that, on an average, the performance of adaptive GA is better than that of the traditional GA. ©2008 IEEE.

关键词： Transfer functions

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Efficient Rate Control Algorithm for Multi-view Video Coding

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China communications 2011年第3期8卷 83-89页

作者：刘峰熊婕范晶晶林琼洁 Image Processing & Image Communication Key Lab of Jiangsu Province Nanjing University of Posts and Telecommunications Key Lab of Broadband Wireless Communication and Sensor Network Technology(Nanjing University of Posts and Telecommunications) Ministry of Education

Rate control is one of the key factors influencing the multi-view video ***,there is not a rate control algorithm in the existing Joint Multi-view Video Coding *** this paper,an efficient rate control algorithm and a bit allocation strategy for multi-view video coding are *** order to obtain the consistent view quality,a bit allocation model based on the Lagrange optimum algorithm is firstly ***,considering the encoding statistical characteristics of different view types,a view weighting factor is introduced,and it will help improve the precision of bit allocation among *** with the fixed QP control strategy,experiment results show that the proposed algorithm can efficiently control the bit rate and obtain more consistent views,with video visual quality improved.

关键词： rate control rate distortion bit allocation view weighting factor

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A Novel Method to Get Super-Resolution images from Low-Resolution Compressed Video

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The Journal of China Universities of Posts and Telecommunications 2005年第2期12卷 50-54页

作者： ZHOU Liang ZHU Xiu-chang Information Industry Ministry and Jiangsu Province Key Lab of Image Processing and Image Communication Nanjing University of Posts and Communications Nanjing 210003 P. R. China

In order to resolve the problems of discontented restoration effect and confined applying scope which exist in the current compressed video restoration algorithms, a novel method to get super-resolution images from low-resolution compressed video is proposed in this paper. At first, a uniform model is presented and the restoration problem in the Bayesian framework is formulated under the MAP criterion, then the focus is put on the hybrid motion-compensation and transform coding schemes, at last the methods of getting the parameters are provided. The results of the simulation clearly demonstrate that our method not only has the properties of finer vision effect and wider applying scope, but also performs better than those of current classical algorithms in the aspects of Peak Signal Noise Ratio （PSNR） under the basis of the same condition.

关键词： super-resolutlon compressed video restoration

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Expression Recognition Based on Attention Mechanism and Length Feature of Facial Landmark 13

Expression Recognition Based on Attention Mechanism and Leng...

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13th International Conference on wireless communications and Signal processing, WCSP 2021

作者： Yang, Qian Liu, Feng Zhao, Zhenglai Nanjing University of Posts and Telecommunications Nanjing China Nanjing University of Posts and Telecommunications Jiangsu Key Lab of Image Processing Image Communications Nanjing China

ISBN: (纸本)9781665407854

In view of the fact that the proportion of face in the whole image is small and the face posture is skew, which leads to the low accuracy of facial expression recognition, this paper proposes a two-branch neural network based on attention mechanism and length feature of facial landmark. The first branch is based on the modified VGG19 and the integration of the convolutional block attention module (CBAM), which focuses on the extraction of important features of expression. The second branch extracts 68 feature points from the face image, and calculates the Euler distance between these feature points to acquire the length information of 2278 dimensions, and is finally normalized and fed into the full connection layer. The network composed of the first branch and the second branch is trained by joint fine-tuning, where L2 regularization is added to prevent overfitting. The proposed method is tested and verified on Jaffe, CK + and FER +, and the highest accuracy is 93.48%,96.12% and 84.73% respectively. The performance of the proposed method is more advance than many existing algorithms, which shows that the proposed model has good accuracy and robustness. © 2021 IEEE.

关键词： Face recognition

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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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Mixed image de-noising method of Bayesian estimation and wavelet based on alpha-stable distribution

Mixed image de-noising method of Bayesian estimation and wav...

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2008 IEEE International Conference Neural Networks and Signal processing, ICNNSP

作者： Zhijian, Wang Xuelong, Hu Cheng, Li Liping, Wang School of Information Engineering Yangzhou University Yangzhou Jiangsu 225009 China Jiangsu Province Key Lab. for Image Processing and Image Communication Nanjing University of Posts and Communications Nanjing Jiangsu 210003 China Yangzhou Jiangsu 225001 China

ISBN: (纸本)9781424423118

This paper introduces a new kind of recovery method which is the combination of Bayesian estimation and wavelet threshold. Wavelet coefficients of signals show strong characteristics of the non-Gauss statistics, its probability density function can be modeled by alpha-stable priori distribution. This paper uses Bayesian estimation to obtain the low frequency coefficients, and deals with high frequency coefficients with the wavelet soft threshold, then restore signal by wavelet inverse transform. Bayesian estimation well retains the marginal information of signals, but the signal is still not very smooth recovery and wavelet soft threshold can maintain smooth characteristic. The mixed noise elimination methods of Bayesian estimation and wavelet enhance the peak SNR much greater than wavelet threshold, which has better recovery effect. ©2008 IEEE.

关键词： Probability density function

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A camera self-calibration method based on dual constraints of multi-view images

A camera self-calibration method based on dual constraints o...

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2011年无线通信与信号处理国际会议(WCSP 2011)

作者： Feng Liu Weiwei Han Qiong Xu Jingjing Fan Qiongjie Lin Image Processing and Image Communication Jiangsu Key Laboratory Key Lab of Broadband Wireless Commun Image Processing and Image Communication Jiangsu Key Laboratory

Camera calibration is the essential step of obtaining 3D information from 2D views in the field of computer vision, which is widely used in the area of 3D reconstruction, navigation, visual supervision, etc. A camera self-calibration method based on dual constraints of multi-view images is proposed to make calibration possible when there is no reference calibration block or the movement of camera is arbitrary. In this method, multi-view images are preprocessed first to select three images which are most suitable for camera self-calibration, then we use the method based on the genetic algorithm, the camera parameters are finally estimated by using epipolar geometry matching error and reprojection error as fitness functions as two steps. Experimental results show that the proposed camera self-calibration method is correct and effective.

关键词： multi-view images camera calibration dual constraints genetic algorithm epipolar geometry reprojection error

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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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Approaches to image retrieval using fuzzy set theory

Approaches to image retrieval using fuzzy set theory

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2008 IEEE International Conference Neural Networks and Signal processing, ICNNSP

作者： Li, Yang Xuelong, Hu Jun, Pan School of Information Engineering Yangzhou University Yangzhou Jiangsu 225009 China Jiangsu Province Key Lab. for Image Processing and Image Communication Nanjing University of Posts and Communications Nanjing Jiangsu 210003 China Jiangsu Prov. Key Lab. for Computer Information Processing Technology Suzhou University Suzhou Jiangsu 215006 China

ISBN: (纸本)9781424423118

This paper mainly presents two approaches for image retrieval. There is some faintness in color locating in quantification boundary when image color is quantized. The membership function in fuzzy set theory can describe the fuzzy transition preferably. In this paper, the membership function in HSI color space is adopted to solve the problem above. At the same time, spatial information is integrated with color feature to describe the image content more truly. Due to the importance of texture feature, gray concurrence matrix is extracted. In the second part of this paper, retrieval scheme combining four image feature descriptors is presented, and then follows Fuzzy Hamming Distance (FHD) which is used as a fuzzy similarity measure. We have performed an experiment on a 1000 images database and our results show higher retrieval accuracy. © 2008 IEEE.

关键词： Fuzzy sets

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Video object matching based on sift algorithm

Video object matching based on sift algorithm

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2008 IEEE International Conference Neural Networks and Signal processing, ICNNSP

作者： Xuelong, Hu Yingcheng, Tang Zhenghua, Zhang School of Information Engineering Yangzhou University Yangzhou Jiangsu 225009 China Jiangsu Prov. Key Lab for Image Processing and Image Communication Nanjing University of Posts and Communications Nanjing Jiangsu 210003 China Jiangsu Prov. Key Lab. for Computer Information Processing Technology Suzhou University Suzhou Jiangsu 215006 China

ISBN: (纸本)9781424423118

SIFT (Scale Invariant Feature Transform) is used to solve visual tracking problem, where the appearances of the tracked object and scene background change during tracking. The implementation of this algorithm has five major stages: scale-space extrema detection;keypoint localization;orientation assignment;keypoint descriptor;keypoint matching. From the beginning frame, object is selected as the template, its SIFT features are computed. Then in the following frames, the SIFT features are computed. Euclidean distance between the object's SIFT features and the frames' SIFT features can be used to compute the accurate position of the matched object. The experimental results on real video sequences demonstrate the effectiveness of this approach and show this algorithm is of higher robustness and real-time performance. It can solve the matching problem with translation, rotation and affine distortion between images. It plays an important role in video object tracking and video object retrieval. © 2008 IEEE.

关键词： Tracking (position)

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