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International Conference on Innovative Computing, Information and Control (ICICIC)

作者： Zhong-qiang Xu Xiu-chang Zhu Ministry Strategic Key Laboratory of Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing China

Super-resolution (SR) technique is to estimate the high-resolution (HR) images by combining the non-redundant information that is available into a set of low-resolution (LR) images, which has been a great focus for compressed video. Based on the theory of projection onto convex set (POCS), this paper constructs quantization constraint set (QCS) using the motion between the frames and the quantization information embedded from the video bit stream. By combing the statistical properties of image and the human visual system (HVS), a novel adaptive quantization constraint set (AQCS) is proposed. The proposed algorithm and its performance analysis are also described. Simulation results show that AQCS-based SR algorithm obtains better performance in both objective and subjective quality, which is applicable for compressed video

关键词： Video compression Quantization image coding Strontium image reconstruction image resolution Focusing Constraint theory Streaming media Humans

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Stereo matching using aggregated likelihood and multi-scale prior

Stereo matching using aggregated likelihood and multi-scale ...

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International Conference on Audio, Language and image processing, ICALIP

作者： Liang Wang Tianliang Liu Xiuchang Zhu Jiangsu Provincial Key Laboratory of Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781467301732

This paper proposes a novel global stereo matching method using aggregated likelihoods and multi-scale priors. The likelihoods of dense stereo correspondences as data term can be robustly expressed by aggregated matching costs based on Weber feature descriptors in an asymmetrical linear filtering model. The multi-scale priors on disparity surface are designed to capture scene smooth term from larger neighborhood besides 4-connected neighborhood. The presented stereo approach being relatively simple does not rely on image segmentation and any scene semantic analysis. Experiments demonstrate that the proposed stereo matching algorithm can produce the dense smooth disparity results comparable to those of excellent stereo matching techniques.

关键词： Stereo vision Visualization Robustness image segmentation Algorithm design and analysis Computer vision image color analysis

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Learning distance metric for regression by semidefinite programming with application to human age estimation 09

Learning distance metric for regression by semidefinite prog...

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17th ACM International Conference on Multimedia, MM'09, with Co-located Workshops and Symposiums

作者： Xiao, Bo Yang, Xiaokang Xu, Yi Zha, Hongyuan Institute of Image Communication and Information Processing Shanghai Key Laboratory of Digital Media Processing and Transmission Shanghai Jiaotong University Shanghai 200240 China College of Computing Georgia Institute of Technology Atlanta GA 30332 United States

ISBN: (纸本)9781605586083

A good distance metric for the input data is crucial in many pattern recognition and machine learning applications. Past studies have demonstrated that learning a metric from labeled samples can significantly improve the performance of classification and clustering algorithms. In this paper, we investigate the problem of learning a distance metric that measures the semantic similarity of input data for regression problems. The particular application we consider is human age estimation. Our guiding principle for learning the distance metric is to preserve the local neighborhoods based on a specially designed distance as well as to maximize the distances between data that are not in the same neighborhood in the semantic *** any assumption about the structure and the distribution of the input data, we show that this can be done by using semidefinite programming. Furthermore, the low-level feature space can be mapped to the high-level semantic space by a linear transformation with very low computational cost. Experimental results on the publicly available FG-NET database show that 1) the learned metric correctly discovers the semantic structure of the data even when the amount of training data is small and 2) significant improvement over the traditional Euclidean metric for regression can be obtained using the learned metric. Most importantly, simple regression methods such as k nearest neighbors (kNN), combined with our learned metric, become quite competitive (and sometimes even superior) in terms of accuracy when compared with the state-of-the-art human age estimation approaches. Copyright 2009 ACM.

关键词： Clustering algorithms

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A novel supervised bimodal emotion recognition approach based on facial expression and body gesture

A novel supervised bimodal emotion recognition approach base...

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作者： Yan, Jingjie Lu, Guanming Bai, Xiaodong Li, Haibo Sun, Ning Liang, Ruiyu Jiangsu Provincial Key Laboratory of Image Processing and Image Communication College of Telecommunications and Information Engineering Nanjing University of Posts and Telecommunications Nanjing210003 China Engineering Research Center of Wide Band Wireless Communication Technology Nanjing University of Posts and Telecommunications Nanjing211167 China School of Communication Engineering Nanjing Institute of Technology Nanjing211167 China

In this letter, we propose a supervised bimodal emotion recognition approach based on two important human emotion modalities including facial expression and body gesture. A effectively supervised feature fusion algorithms named supervised multiset canonical correlation analysis (SMCCA) is presented to established the linear connection between three sets of matrices, which contain the feature matrix of two modalities and their concurrent category matrix. The test results in the bimodal emotion recognition of the FABO database show that the SMCCA algorithm can get better or considerable efficiency than unsupervised feature fusion algorithm covering canonical correlation analysis (CCA), sparse canonical correlation analysis (SCCA), multiset canonical correlation analysis (MCCA) and so on. © 2018 The Institute of Electronics, Information and communication Engineers.

关键词： Emotion Recognition

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Robust piecewise planar stereo with modified segmentation cues in urban scenes

Robust piecewise planar stereo with modified segmentation cu...

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International Conference on Multimedia Technology

作者： Zengtao Jiao Tianliang Liu Xiuchang Zhu Jiangsu Provincial Key Laboratory of Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing China

This paper proposes a robust piecewise planar multi view stereo (MVS) approach specifically designed for urban scenes. These architectural scenes are problematic for traditional computer vision methods. In our work, we focus on exploiting some useful constraints of artificial structures such as piecewise coplanarity and boundaries of superpixels. Firstly, we reconstruct quasi-dense 3D point clouds of urban scenes using patches-based MVS (PMVS) method. Secondly, a set of 3D candidate planes are generated by the obtained point clouds without any assumption on the normals of planes, unlike famous Manhattan-world assumption. Then, we segment multi-view images with watershed algorithm and modify the contours of superpixels by the classical Douglas-Peucker approximation algorithm to fit the contours to the boundaries of objects in urban scenes as much as possible. Finally, we use the candidate planes as labels and superpixels as nodes to formulate our Markov Random Field (MRF) optimization problem, then a piecewise planar depth map for each view is recovered by solving the optimization problem using graph-cuts. Experiments show that our method outperforms previous approaches in terms of accuracy.

关键词： Three dimensional displays image segmentation Computer vision Stereo vision Approximation methods image reconstruction Optimization

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Identification of various food residuals on denim based on hyperspectral imaging system and combination optimal strategy

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Artificial Intelligence in Agriculture 2021年第1期5卷 125-132页

作者： Yuzhen Chen Ziyi Xu Wencheng Tang Menghan Hu Douning Tang Guangtao Zhai Qingli Li Shanghai Key Laboratory of Multidimensional Information Processing School of Communication&Electronic EngineeringEast China Normal UniversityShanghai 200062China School of Statistics East China Normal UniversityShanghai 200062China Institute of Image Communication and Information Processing Shanghai Jiao Tong UniversityShanghai 200240China McCormick School of Engineering Northwestern UniversityEvanstonILUnited States

As the science and technology develop,crime methods and scenes have become increasingly complex and *** evidence analysis has become amore and more important criminal investigation technology and liquid is the main form of trace *** can provide not only energy,but clues to solve *** this study,we build a hyperspectral imaging system to detect liquid residue traces,including apple juice,coffee,cola,milk and tea,on denims with light,middle and dark *** obtained hyperspectral images are first subjected to spectral calibration and hyperspectral data ***,Partial Least Squares(PLS)is applied to select the informative wavelengths from the preprocessed *** modeling phase,the combination optimal strategy,support vector machine(SVM)combined with random forest(RF),is developed to establish classification *** experimental results demonstrate that the combination optimal model can achieve TPR,FPR,Precision,Recall,F1,and AUC of 83.5%,2.30%,79.7%,83.5%,81.6%,and 94.7%for classifying fabrics contaminated by various food *** respect to the classification of liquid and fabric types,the combination optimalmodel also yields satisfactory classification *** future work,wewill expand the types of liquid,and make appropriate adjustment to algorithms for improving the robustness of classification *** research may play a positive role in the construction of a harmonious society.

关键词： Hyperspectral imaging Food residual on denim Combination optimal strategy Variable selection Forensic application

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A Video Code Based on Distribution Compressive Sensing

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Procedia Engineering 2012年 29卷 3613-3618页

作者： Wu Ming-hu Zhu Xiu-chang Jiangsu Province Key Lab on Image Processing & Image Communication Nanjing University of Posts and Telecommunications Nanjing China School of Electrical and Electronic Engineering Hubei University of Technology Wuhan China

Compressed sensing (CS) is a new technique for simultaneous data sampling and compression. In this paper, we propose a new video coding algorithm based on Distributed Compressive Sampling(DCS) principles, where almost all computation burdens can be shifted to the decoder, resulting in a very lowcomplexity encoder. At the decoder, compressed video can be efficiently reconstructed. Our algorithm can be useful in those video applications that require very low complex encoders. Simulation results show that our scheme compares favorably with existing schemes at a much lower implementation cost.

关键词： Distributed Compressive Sampling sparsity distributed video coding

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Coarse carrier and timing synchronization for interleaved OFDMA uplink system

Coarse carrier and timing synchronization for interleaved OF...

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2010 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2010

作者： Miao, Ruiqin Sun, Jun Gui, Lin Xiong, Jian Institute of Image Communication and Information Processing Department of Electronic Engineering Shanghai Jiao Tong University Shanghai 200240 China Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9781424444625

In orthogonal frequency division multiple access (OFDMA) uplink system, estimations of time delay and carrier frequency offset (CFO) are both particularly challenging. In this paper, a coarse CFO and time delay estimation method is proposed for interleaved OFDMA uplink system. By exploiting the special scheme of interleaved OFDMA, the repetitive time-domain training symbol is designed, and the training sequences for different users have good autocorrelation and cross-correlation properties. Furthermore, the time delay and CFO estimation metrics are presented by making certain correlation between the received training symbol and the local sequence. Through searching peak of the proposed metrics, integral CFO of many subcarriers spaces for each user can be estimated, and then timing delay for each user can be found. Simulations illustrate the proposed estimation scheme can get good performance under multipath channel.

关键词： Frequency division multiple access

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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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OCF-Layout2Img: Object-Wise Constraint Free Layout to image Generation 23

OCF-Layout2Img: Object-Wise Constraint Free Layout to Image ...

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15th International Conference on Digital image processing, ICDIP 2023

作者： Lin, Xiao Liu, Bin He, Zhifen Wang, Kang Li, Bo School of Mathematics and Information Science Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Nanchang Hangkong University China Jiangxi Science and Technology Infrastructure Center Jiangxi Computing Center China

ISBN: (纸本)9798400708237

Complex scene generation is an important and challenging image synthesis task. Though latent space based conditional generative methods get impressive results, the accurate locating of objects for more detailed situation and editable contiguous synthesis are still a snag. In addition, previous methods with spatial awareness are easy to lose the location information after a series fusion operation. Focusing on such kind of problems, in this paper we propose an object-wise constraint free and location-lossless way of layout embedding by combining VAE and recent high performance VQGAN to achieve a location accurate and stable synthesis for layouts of complex scene. Instead of conditioning on layout, we apply a pretrained VQGAN to define the latent space and project every region of layout to image latent space directly by aligning their distribution with a novel light Cross-VAE structure. Then the quantization and decoder of VQGAN are reused for synthesis. This VAE plugged into VQGAN framework, which is called Layout-DVGAN in this paper. Experimental results demonstrate our method has competitive performance compared with the approaches which applied explicit spatial awareness way. © 2023 ACM.

关键词： Location

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