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检索条件"机构=The Provincial Key Lab of Image Processing and Image Communications"

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Robust piecewise planar stereo with modified segmentation cues in urban scenes

Robust piecewise planar stereo with modified segmentation cu...

引用

2nd International Conference on Multimedia Technology, ICMT 2011

作者： Jiao, Zengtao Liu, Tianliang Zhu, Xiuchang Jiangsu Provincial Key Lab. of Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing 210003 China

ISBN: (纸本)9781612847740

This paper proposes a robust piecewise planar multiview 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. © 2011 IEEE.

关键词： Superpixels

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An efficient fast inter mode decision algorithm for h.264/avc ***

An efficient fast inter mode decision algorithm for h.264/av...

引用

2009 WRI International Conference on communications and Mobile Computing, CMC 2009

作者： Huang, Huaibin Hu, Dong Key Lab. of Image Processing and Image Communications of Jiangsu Province Nanjing University of Posts and Telecom Nanjing 210003 China

ISBN: (纸本)9780769535012

An efficient fast inter mode decision algorithm for the baseline H.264/AVC video coding is proposed in this paper. The main idea of the algorithm is to reduce the number of candidate modes for Rate Distortion Optimization(RDO) by using early mode detection in four different levels, viz. SKIP mode detection, type detection at macroblock-level, type detection at submacroblock-level and intra modes detection. In addition, the correlation of cost of current MB and the one of previous frame, as well as the cost's monotonous property are both used to help the mode decision. Compared to JM8.6 reference software, our algorithm can save encoding time 71.743% on average with negligible PSNR loss, which is very helpful for H.264/AVC inter frame encoding. © 2009 IEEE.

关键词： Electric distortion

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Partical swarm optimization based unequal loss protection of embedded video streams

Partical swarm optimization based unequal loss protection of...

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2010 IEEE 12th International Conference on Communication Technology, ICCT'2010

作者： Hu, Jiajing Hu, Dong Key Lab. of Image Processing and Image Communications of Jiangsu Province Nanjing University of Posts and Telecom Nanjing 210003 China

ISBN: (纸本)9781424468690

This paper presents a new scheme for optimal packetization of scalable multimedia data over lossy network. By assigning an unequal amount of forward error correction (FEC) bits to each segment of transmission packets, the proposed algorithm protects a progressive bitstream generated by a three-dimensional set partitioning in hierarchical trees (3-D SPIHT) algorithm. The partical swarm optimization (PSO) algorithm is used to reasonably allocate bits between source coding and channel coding across packets. Experimental results show that the proposed algorithm provides close to optimal average peak signal-to-noise ratio performance and that its'running time is significantly lower than that of previously known solution. © 2010 IEEE.

关键词： Signal to noise ratio

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Sleep electroencephalogram analysis based on symbolic transfer entropy

引用

2013 International Conference on Advances in Materials Science and Manufacturing Technology, AMSMT 2013

作者： Chang, Rui Jun Liu, Yang Chen, Qiu Ping Wang, Jun Image Processing and Image Communications Key Lab College of Geo and Bio Information Nanjing Univ of Posts and Telecomm Nanjing 210003 China

ISBN: (纸本)9783037857984

The quality of sleep has a great relationship with health. The result of sleep stage classification is an important indicator to measure the quality of sleep. It was found that the symbolic transfer entropy about wake and the first stage of non-rapid eye movement sleep reflect on the changes of sleep stage. And it was confirmed by T test and multi-samples experiments. The symbolic transfer entropy can apply into automatic sleep stage classification. By Multi-parameter analysis it could achieve a higher accuracy of sleep stage classification. © (2013) Trans Tech Publications, Switzerland.

关键词： Electroencephalography

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Pathological electrocardiogram analysis based on symbolic relative entropy

Pathological electrocardiogram analysis based on symbolic re...

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2013 International Conference on Bio-Medical Materials and Engineering, ICBME 2013

作者： Qiu, Jia Kai Huang, Xiao Liang Chang, Su Yi Wang, Yun Xia Wang, Jun Image Processing and Image Communications Key Lab College of Geo and Bio Information Nanjing Univ of Posts and Telecomm Nanjing 210003 China

ISBN: (纸本)9783037857557

In this paper, symbolic relative entropy was used to analyze normal electrocardiogram (ECG), the ECG taken from patient with congestive heart failure (CHF) and Atrial fibrillation (AF). Statistical testing showed that the symbolic relative entropy of normal ECG was distinctly higher than that of CHF while the symbolic relative entropy of CHF was distinctly higher than that of AF. It discoved that symbolic relative entropy can be used to analyze the different pathological ECG which could be used to assisted clinical diagnosis. © (2013) Trans Tech Publications, Switzerland.

关键词： Electrocardiograms

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Detrended cross-correlation analysis of epilepsy electroencephalagram singals

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2013 International Conference on Advances in Materials Science and Manufacturing Technology, AMSMT 2013

作者： Zhao, Jun Chang Dou, Wan Hu Ji, Hong Da Wang, Jun Image Processing and Image Communications Key Lab College of Geo and Bio Information Nanjing Univ of Posts and Telecomm Nanjing 210003 China

ISBN: (纸本)9783037857984

The cross-correlation performance between epilepsy electroencephalogram (EEG) signals reflects the status of epilepsy patients which has importance for analyzing long-range correlation of non-stationary signals. For the first time, detrended cross-correlation analysis (DCCA) was applied to analyze different physiological and pathological states of epilepsy EEG signals. It were compared the difference of DCCA values between epilepsy patients' EEG signals and normal subjects' EEG signals. It was found that the DCCA values of epilepsy patients' EEG signals increased compared the normal subjects' EEG signals which can be helpful for medical diagnosis and treatment. © (2013) Trans Tech Publications, Switzerland.

关键词： Electroencephalography

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Symbolic dynamics analysis of pathological signals

Symbolic dynamics analysis of pathological signals

引用

2011 1st International Workshop on Complexity and Data Mining, IWCDM 2011

作者： Wang, Jun Wu, Jun Image Processing and Image Communications Key Lab. School of Geography and Biological Information Nanjing Univ. of Posts and Telecomm Nanjing 210003 China

ISBN: (纸本)9781457720079

Paper uses symbolic dynamics to study heartbeat time series from the normal subjects, patients with congestive heart failure and cardiac arrest patients. The results show that entropy value of normal people's heart beat signals is the maximum. Information entropy value of congestive heart failure patient is decreasing. Cardiac arrest patients' information entropy is the smallest. It is corresponding that patients have entered into dangerous stage in clinical. Clinical treatment of patients at this time is a critical period. The results are of great significance on the clinical automatically diagnosis. It can play a role in timely warning especially in the long ambulatory ECG monitoring to save the patient's life. © 2011 IEEE.

关键词： Diagnosis

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Enhancing Deep Learning-based Depression Level Estimation Based on Multi-task Learning 24

Enhancing Deep Learning-based Depression Level Estimation Ba...

引用

7th International Conference on Machine Learning and Machine Intelligence, MLMI 2024

作者： Ye, Qingxin Xie, Zhenming Sun, Hao Xin, Luyao Chen, Youwen Song, Jian Chen, Yen-Wei Provincial key Laboratory of Computational Science Huaqiao University Quanzhou China Intelligent Image Processing Lab Zhejiang University Hangzhou China Intelligent Image Processing Lab Ritsumeikan University Osaka Japan

ISBN: (纸本)9798400717833

In recent years, depression, as a serious mental illness, has received widespread attention from various sectors of society. How to identify depressive emotions in a timely manner and detect depression has become an urgent issue that needs to be addressed. Currently, many experts and scholars propose using deep learning methods to assess the level of depression. Compared to other deep learning models, Transformer models have parallel computing capabilities with their self-attention mechanism, enabling them to handle entire sequences and capture long-distance dependencies. After the success of Transformers in natural language processing, similar architectures have been introduced into the field of computer vision, promoting advancements in multi-modal research. However, how to integrate other information or tasks to improve assessment accuracy remains a challenge. In our team's preliminary work, we proposed a multi-modal adaptive fusion Transformer network for assessing depression levels. Inspired by multi-task learning, we introduced gender classification as a second auxiliary task alongside the main task of depression regression, forming a three-task learning framework including depression classification. This was done to enhance the model's performance. We validated the effectiveness of the proposed method by testing it on a public dataset (AVEC 2019 Detecting Depression with AI Sub-challenge). The experimental results show that our proposed method achieved a Concordance Correlation Coefficient (CCC) of 0.60448, which is 1.688% higher than the accuracy of the dual-task learning method (CCC = 0.5876). © 2024 Copyright held by the owner/author(s).

关键词： Multi-task learning

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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...

引用

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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A simplified 3D gaze tracking technology with stereo vision

A simplified 3D gaze tracking technology with stereo vision

引用

2010 International Conference on Optoelectronics and image processing, ICOIP 2010

作者： Zhang, Ke Zhao, Xinbo Ma, Zhong Man, Yi Shaanxi Provincial Key Lab. of Speech and Image Information Processing Northwestern Polytechnical University Xi'an China

ISBN: (纸本)9780769542522

A simplified 3D gaze tracking technology with stereo vision has been developed in this paper. A pair of stereo cameras and two point light sources are used to estimate 3D gaze of user's eye. Compared with other 3D systems, there are two improvements to simplify the whole system in this paper: First, 3D gaze is estimated as the line linking 3D cornea center and the virtual image of pupil center using the first Purkinje images of two LEDs, and no any user-dependent parameters are used in our paper, which require a complicated calibration procedure for each user. Second, to compute the gaze point on screen by intersecting the estimated 3D gaze, the positions of LEDs and the monitor need to be calibrated in advance. By introducing a planar mirror, two LEDs and the monitor are calibrated using a simple method without any other devices. Experimental results show that our gaze tracking system achieves an average estimation error of about 3 degree. © 2010 IEEE.

关键词： Human computer interaction

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