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检索条件"任意字段=Conference on Nonlinear Image Processing XI"

共 189 条记录，以下是81-90 订阅

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On pain assessment from facial videos using spatio-temporal local descriptors

On pain assessment from facial videos using spatio-temporal ...

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Workshops on image processing Theory, Tools and Applications, IPTA

作者： Ruijing Yang Shujun Tong Miguel Bordallo Elhocine Boutellaa Jinye Peng xiaoyi Feng Abdenour Hadid Department of Information Science and Technology Northwest University Xi'an China School of Electronics and Information Northwestern Polytechnical University Xi'an China Center For Machine Vision and Signal Analysis University of Oulu Finland Centre de Développement des Technologies Avancées Algeria

ISBN: (纸本)9781467389112

Automatically recognizing pain from spontaneous facial expression is of increased attention, since it can provide for a direct and relatively objective indication to pain experience. Until now, most of the existing works have focused on analyzing pain from individual images or video-frames, hence discarding the spatio-temporal information that can be useful in the continuous assessment of pain. In this context, this paper investigates and quantifies for the first time the role of the spatio-temporal information in pain assessment by comparing the performance of several baseline local descriptors used in their traditional spatial form against their spatio-temporal counterparts that take into account the video dynamics. For this purpose, we perform extensive experiments on two benchmark datasets. Our results indicate that using spatio-temporal information to classify video-sequences consistently shows superior performance when compared against the one obtained using only static information.

关键词： Pain Feature extraction Videos Maximum likelihood detection nonlinear filters Video sequences Support vector machines

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Readability enhancement of low light images based on dual-tree complex wavelet transform

Readability enhancement of low light images based on dual-tr...

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International conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Tingting Sun Cheolkon Jung School of Electronic Engineering Xidian University Xi'an China

ISBN: (纸本)9781479999897

Since images captured under low light conditions have low dynamic range and are seriously degraded by noise, it is a challengeable task to achieve both contrast enhancement and noise reduction from low light images. In this paper, we propose a readability enhancement method of low light images based on dual-tree complex wavelet transform (DTCWT). We perform contrast enhancement and noise reduction for low light images based on wavelet coefficients. First, we conduct illumination compensation to contain fine details and fully utilize dynamic range. Then, we decompose the image into high-pass and low-pass sub-bands by DTCWT, and perform contrast limited adaptive histogram equalization (CLAHE) and a nonlinear transform in low-pass and high-pass sub-bands, respectively, to achieve both contrast enhancement and noise reduction. Finally, we perform color correction to deal with the color distortion problem caused by contrast enhancement. Experimental results demonstrate that the proposed method outperforms state-of-the-art ones in contrast enhancement, noise reduction, and color reproduction in terms of both subjective and objective evaluations.

关键词： Decision support systems Transforms image color analysis

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Perceptual image quality in normalized LOG domain for Adaptive Optics image post-processing

Perceptual image quality in normalized LOG domain for Adapti...

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International conference on Optical Instruments and Technology - Optoelectronic Imaging and processing Technology

作者： Guo, Shiping Zhang, Rongzhi Li, Jisheng Zou, Jianhua Liu, Changhai Gao, Weizhe Xi An Jiao Tong Univ Jiaoda Cooperat Dept SKL Astronaut Dynam Xian 710049 Shaanxi Peoples R China Xian Satellite Control Ctr State Key Lab Astronaut Dynam Xian 710043 Shaanxi Peoples R China

ISBN: (纸本)9781628418033

Adaptive Optics together with subsequent post-processing techniques obviously improve the resolution of turbulence-degraded images in ground-based space objects detection and identification. The most common method for frame selection and stopping iteration in post-processing has always been subjective viewing of the images due to a lack of widely agreed-upon objective quality metric. Full reference metrics are not applicable for assessing the field data, no-reference metrics tend to perform poor sensitivity for Adaptive Optics images. In the present work, based on the Laplacian of Gaussian (LOG) local contrast feature, a nonlinear normalization is applied to transform the input image into a normalized LOG domain;a quantitative index is then extracted in this domain to assess the perceptual image quality. Experiments show this no-reference quality index is highly consistent with the subjective evaluation of input images for different blur degree and different iteration number.

关键词： Adaptive Optics post-processing image quality assessment imaging through turbulence

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Dehazing Method through Polarimetric Imaging and Multi-Scale Analysis 11

Dehazing Method through Polarimetric Imaging and Multi-Scale...

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conference on Satellite Data Compression, Communications, and processing xi

作者： Cao, Lei Shao, xiaopeng Liu, Fei Wang, Lin Xidian Univ Sch Phys & Optoelect Engn Xian 710071 Shaanxi Peoples R China

ISBN: (纸本)9781628416176

An approach for haze removal utilizing polarimetric imaging and multi-scale analysis has been developed to solve one problem that haze weather weakens the interpretation of remote sensing because of the poor visibility and short detection distance of haze images. On the one hand, the polarization effects of the airlight and the object radiance in the imaging procedure has been considered. On the other hand, one fact that objects and haze possess different frequency distribution properties has been emphasized. So multi-scale analysis through wavelet transform has been employed to make it possible for low frequency components that haze presents and high frequency coefficients that image details or edges occupy are processed separately. According to the measure of the polarization feather by Stokes parameters, three linear polarized images (0 degrees, 45 degrees, and 90 degrees) have been taken on haze weather, then the best polarized image I-min and the worst one I-max can be synthesized. Afterwards, those two polarized images contaminated by haze have been decomposed into different spatial layers with wavelet analysis, and the low frequency images have been processed via a polarization dehazing algorithm while high frequency components manipulated with a nonlinear transform. Then the ultimate haze-free image can be reconstructed by inverse wavelet reconstruction. Experimental results verify that the dehazing method proposed in this study can strongly promote image visibility and increase detection distance through haze for imaging warning and remote sensing systems.

关键词： haze-removal image restoration polarmetric imaging muti-scale analysis remote sensing

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Deep neural network and switching Kalman filter based continuous affect recognition

Deep neural network and switching Kalman filter based contin...

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IEEE International conference on Multimedia and Expo Workshops (ICMEW)

作者： Ercheng Pei xiaohan xia Le Yang Dongmei Jiang Hichem Sahli School of Computer Science Shaanxi Key Lab on Speech and Image Information Processing Xi'an China Dept. ETRO Vrije Universiteit Brussel (VUB) Brussels NPU-VUB Joint AVSP Lab Interuniversity Microelectronics Centre Heverlee Belgium

ISBN: (纸本)9781509015535

In this paper, we propose the deep neural network - switching Kalman filter (DNN-SKF) based frameworks for both single modal and multi-modal continuous affective dimension estimation. The DNN-SKF framework firstly models the complex nonlinear relationship between the input (audio, visual, or lexical) features and the affective dimensions via the non-recurrent DNN, then models the temporal dynamics embedded in the emotions via the segmental linear SKF. Affective dimension estimation experiments are carried out on the Audio Visual Emotion Challenge (AVEC2012) database. Single modal estimation results are compared to those from the Support Vector Regression (SVR) models and Bidirectional Long Short-Term Memory Recurrent Neural Network (BLSTM-RNN) models, results show that for all modalities, and for all affective dimensions except for arousal from the audio features, the DNN-SKFs outperform SVR and BLSTM-RNN models in estimating the affective dimensions. Multi-modal estimation results are compared with the state of the art results on the competition of AVEC2012. Results show that both on the development set and test set, the proposed DNN-SKF models obtain the best performance in estimating the affective dimensions. On the test set, with the audio visual features, the average Pearson correlation coefficient (COR) is improved to 0.326 from 0.226 of the linear regression method [1], while with the audio visual and lexical features, the COR is improved to 0.355 from 0.344 of the particle filter fusion method (SVR-PF) [2].

关键词： Estimation Visualization Switches Kalman filters Hidden Markov models Training Feature extraction

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image processing and Analysis Based on Partial Differential Equation Method

Image Processing and Analysis Based on Partial Differential ...

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2015 4th National conference on Electrical,Electronics and Computer Engineering(NCEECE 2015)

作者： Yeyang Jiang Tianfu Chai Jiangxi Science & Technology Normal University

ISBN: (纸本)9781510819085

This paper analyzes the characteristics of image processing method based on nonlinear evolution equations, expounds the advantages, mechanism and theoretical basis of nonlinear evolution equations model in image processing algorithm, and uses the method of partial differential equation for image denoising and edge sharpening(Deblurring), image resolution enhancement, image shaping and image measurement.

关键词： image proeessing PDE image feature detection

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image QUALITY ASSESSMENT WITH MEAN SQUARED ERROR IN A LOG BASED PERCEPTUAL RESPONSE DOMAIN 2

IMAGE QUALITY ASSESSMENT WITH MEAN SQUARED ERROR IN A LOG BA...

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2nd IEEE China Summit / International conference on Signal and Information processing (IEEE ChinaSIP)

作者： Xue, Wufeng Mou, Xuanqin Xi An Jiao Tong Univ Inst Image Proc & Pattern Recognit Xian 710049 Peoples R China

ISBN: (纸本)9781479954032

Up to now, there existing a lot of models that predict subjective quality of the contents of natural images which have undergone some unknown distortion procedures. These models, no matter fall in to the bottom-up mechanism or belong to the top-down functional modelling, fail to provide an easy-applied and reliable solution. The complex computation procedure prevents them from being widely used in related image processing areas such as image enhancement, image reconstruction and video coding. In the present work, we start from a two stage nonlinear perception model, which transforms the input image into a decorrelated one and then further reduces the redundancy between neighboring pixels by another nonlinear normalization procedure which transforms the previous output into a perceptual response domain. The final quality prediction is computed as the Euclid distance of the reference image and the distorted one in this response domain, this will make the new model be readily applied in other areas.

关键词： image quality response domain correlation mutual information

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image quality assessment with mean squared error in a log based perceptual response domain

Image quality assessment with mean squared error in a log ba...

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IEEE China Summit & International conference on Signal and Information processing (ChinaSIP)

作者： Wufeng Xue Xuanqin Mou Institute of Image Processing and Pattern Recognition Xi'an Jiaotong University Xi'an China

关键词： Abstracts Indexes PSNR Visualization image processing

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Research on image vectorization based on dual-thumb pneumatic flexible robot hand

Research on image vectorization based on dual-thumb pneumati...

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4th International conference on Materials Science and Information Technology, MSIT 2014

作者： Wan, Shao Song Cao, Jian Zhu, Qun Song Yan, Cong XiJing University Xi'an Shaanxi Province 710123 China Air Force Engineering University Xi'an Shaanxi Province 710051 China

ISBN: (纸本)9783038351733

Because the traditional linear vectorization methods have some shortcomings including processing data slowly, being sensitive to noises and being easy to be distorted. Fuzzy rules and its inference mechanism are the assurance of achieving feature fusion. This paper has a design and analysis on the dual thumb pneumatic flexible robot hand base on the active flexible bending joints we have developed. The flexible joint is composed of four elongation artificial muscles with parallel arrangement. The robot hand has five multi-actuated fingers each with three flexible joints. To improve the flexibility and stability of grasp, the other four fingers are orthogonal and symmetrical except the middle finger, which forms the dual thumb oriented grasp model. Furthermore, we study on the position and posture of fingers applying the parameterized homogeneous transformation to the large deformation and nonlinear problems of flexible joint. © (2014) Trans Tech Publications, Switzerland.

关键词： Machine design

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Multiscale jensen-shannon divergence based analysis of beta wave attention EEG

Multiscale jensen-shannon divergence based analysis of beta ...

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2014 International conference on Mechanics and Mechatronics, ICMM 2014

作者： Zhang, Zheng xia Xu, Si Qiu Zhou, Er Ning Huang, xiao Lin Wang, Jun Image Processing and Image Communications Key Lab College of Geo and Bio Information Nanjing Univ of Posts and Telecomm Nanjing 210003 China Institute of Biomedical Electronic Engineering School of Electronic Science and Engineering Nanjing University Nanjing 210093 China

ISBN: (纸本)9783038351627

The article adopted the multiscale Jensen-Shannon Divergence analysis method for EEG complexity analysis, then the study found that this method can distinguish between three different status (Eyes closed, count, in a daze) acquisition of Beta EEG time series, shows three different states of Beta EEG time series have significant differences. In each state of the three different states (Eyes closed, count, in a daze), we are aimed at comparing and analyzing the statistical complexity of EEG time series itself and the statistical complexity of EEG time series shuffled data, finding that there are large amounts of nonlinear time series in the Beta EEG signals. This method is also fully proved that the multi-scale JSD algorithm can be used to analyze EEG signals, attention statistical complexity can be used as a measure of brain function parameter, which can be applied to the auxiliary clinical brain function evaluation in the future. © (2014) Trans Tech Publications, Switzerland.

关键词： Time series

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