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2011 4th IEEE International Conference on Computer Science and Information Technology(ICCSIT 2011)

作者： Man Yi Zhao Xinbo Zhang Ke Shaanxi Provincial Key Lab.of Speech & Image Information Processing Northwestern Polytechnical University

ISBN: (纸本)9781612848334

A 3D gaze estimation and tracking algorithm based on facial feature tracking is presented in this ***,we used the Active Shape Model(ASM) to extract facial feature points with a stereo ***,the full 3D pose of head is estimated by comparing the feature points of current pose with initial head *** that,the center of eyeball is obtained based on a 3D eye model which is related to head pose and the middle point of eye ***,optical axis was computed as 3D vectors through the center of eyeball to the center of ***,visual axis was gotten by adding an angle to optical ***,in our system,a one-time personal calibration is used to determine this *** experimental results show the accuracy of our gaze tracking system achieves less than 3 degree.

关键词： gaze tracking gaze estimation head pose facial feature tracking stereo cameras

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未来视频技术专题(英文)

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China communications 2013年第5期 8-10页

作者：陈熙霖朱秀昌王桥胡栋 Ming-Ting SUN the Institute of Computing Technology Chinese Academy of Sciences (CAS) the IEEE Transactions on Image Processing the Journal of Computer Science and Technology the Chinese Journal of Computers College of Communications and Information Engineering NUPT Image Processing and Image Communications Key Laboratory of Information Industrial Ministry and Jiangsu Province Signal and Information Processing Laboratory Southeast University

In the past few years, video has become one of the most powerful engines to push communications forward. The increasing of digital video technology requires larger and larger bandwidth for various applications, such as IPTV, VOD, video phone, mobile search, etc. The goal of this Feature Topic column is to present and highlight the latest progress and future video-related technologies. We hope this

关键词： IEEE over

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Transformer-based Lossless Compression of Aurora Spectral images: A Spatial-Temporal-Spectral Joint Approach 17

Transformer-based Lossless Compression of Aurora Spectral Im...

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17th IEEE International Conference on Signal processing, ICSP 2024

作者： Cao, Xinlong Li, Jiaojiao Li, Yuanqing Yan, Jiapeng Zheng, Zhenxing Xi'an University of Posts & Telecommunications School of Communications and Information Engineering School of Artificial Intelligence Xi'an710121 China Xi'an Key Laboratory of Image Processing Technology and Applications for Public Security Xi'an710121 China International Joint Research Center for Wireless Communication and Information Processing Technology of Shaanxi Province Xi'an710121 China

ISBN: (纸本)9798350387384

Aurora spectral image lossless compression has seen significant advancements in recent years. However, most compression algorithms are based on traditional image compression techniques, focusing solely on spectral and spatial correlations without considering temporal correlations. To further enhance compression performance, this paper proposes a Transformer-based point-by-point prediction algorithm for auroral spectral images, which simultaneously uses spatial, spectral and temporal contexts for prediction. Our prediction network consists of two parts: an encoder and a decoder. The encoder is composed of the encoding unit of the original Transformer and is used to extract features from spatial, spectral and temporal contexts. The decoder consists of fully connected layers and is used for prediction. Experimental results show that the average bitrate of this method is reduced by 0.179 bpp compared with the JPEG2000 algorithm, and the average bitrate is reduced by 0.054 bpp compared with the online DPCM algorithm. © 2024 IEEE.

关键词： image compression

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Blurring length estimation using ringing artifacts in a deblurred image

Blurring length estimation using ringing artifacts in a debl...

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3rd International Conference on image Analysis and Signal processing, IASP 2011

作者： Yang, Shuangxue Liu, Hong Liu, Benyong Liao, Xiang School of Computer Science and Information Institute of Intelligent Information Processing Guizhou University Guiyang 550025 China Key Lab. of Sound-Image Material Examination and Authentication Ministry of Public Security of PRC Guiyang 550001 China

ISBN: (纸本)9781612848808

The restoration quality of a motion-blurred image is highly dependent on the estimation accuracy of the motion blurring parameter. This manuscript presents a novel and precise method for estimation of the motion blurring length, wherein the ringing artifact amount of a deblurred image is measured by energy proportion contained in appropriate frequency bands, and a blurring length with minimum ringing artifact amount is taken as the optimal estimation of the true blurring length. Experimental results show good performance of the proposed algorithm in motion blurring length estimation. © 2011 IEEE.

关键词： image enhancement

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Reliability assessments of Chinese high speed railway network

Reliability assessments of Chinese high speed railway networ...

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2011 IEEE International Conference on Service Operations, Logistics and Informatics, SOLI 2011

作者： Zhang, Jianhua Hong, Liu Wang, Shuliang Xu, Xiaoming Department of Control Science and Engineering Key Lab for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China University of Shanghai for Science and Technology Shanghai Academy of System Science Shanghai 200093 China

ISBN: (纸本)9781457705731

With the economic developments, high speed railway has been paid many attentions in China and medium- short term planning of Chinese high speed railway network has been formed and most of the railways have been started into operations. In this paper, graph theory and complex network theory are adopted to assess the reliability of Chinese high speed railway network. The topological characteristics and real distances between pairs of stations are discussed to investigate the reliability of Chinese high-speed rail network. Several parameters are presented to investigate the topological characteristics and the reliability and robustness of the network subject to failures. The parameter called unit degree betweenness is proposed to assess the transport capacity of lines connecting with the nodes. The largest degree node-based attacks and the highest betweenness node-based attacks are involved into Chinese high speed railway network to assess the topological reliability and robustness. The results show that the highest betweenness node-based attacks are more effective to destroy the network than the largest degree node-based attacks. Moreover, the cumulative degree distribution and the real mileages of railways between pairs of stations can be fitted by Gauss functions, and the distribution of real shortest distances over all pairs of stations of the network is fitted by a normal distribution function. By the simulations, the critical stations, Guangzhou Station, Zhengzhou Station and Jinan Station for the largest degree node-based attacks, and Wuhan Station, Xuzhou Station and Shijiazhuang Station for the highest betweenness node-based attacks, can be obtained in this paper. © 2011 IEEE.

关键词： Graph theory

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Adversarial Refinement Network for Human Motion Prediction 15th

Adversarial Refinement Network for Human Motion Prediction

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15th Asian Conference on Computer Vision, ACCV 2020

作者： Chao, Xianjin Bin, Yanrui Chu, Wenqing Cao, Xuan Ge, Yanhao Wang, Chengjie Li, Jilin Huang, Feiyue Leung, Howard City University of Hong Kong Hong Kong China Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Tencent Youtu Lab Shanghai China

ISBN: (纸本)9783030695316

Human motion prediction aims to predict future 3D skeletal sequences by giving a limited human motion as inputs. Two popular methods, recurrent neural networks and feed-forward deep networks, are able to predict rough motion trend, but motion details such as limb movement may be lost. To predict more accurate future human motion, we propose an Adversarial Refinement Network (ARNet) following a simple yet effective coarse-to-fine mechanism with novel adversarial error augmentation. Specifically, we take both the historical motion sequences and coarse prediction as input of our cascaded refinement network to predict refined human motion and strengthen the refinement network with adversarial error augmentation. During training, we deliberately introduce the error distribution by learning through the adversarial mechanism among different subjects. In testing, our cascaded refinement network alleviates the prediction error from the coarse predictor resulting in a finer prediction robustly. This adversarial error augmentation provides rich error cases as input to our refinement network, leading to better generalization performance on the testing dataset. We conduct extensive experiments on three standard benchmark datasets and show that our proposed ARNet outperforms other state-of-the-art methods, especially on challenging aperiodic actions in both short-term and long-term predictions. © 2021, Springer Nature Switzerland AG.

关键词： Errors

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A video tracking system for limb motion measurement in small animals

A video tracking system for limb motion measurement in small...

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2010 International Conference on Optoelectronics and image processing, ICOIP 2010

作者： Xu, Qi Cai, Cong Zhou, Houlun Ren, Hangkong KEY Lab. of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan China Department of Anatomy Tongji Medical College Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9780769542522

Motion analysis can provide useful information for biomedical researches. In this paper, we have presented a video tracking system for limb motion measurement in small animals. The system employs a consumer-grade video camera to record the locomotion of a rat, which can reduce the cost of the system. Three matching methods are available for different application. Moreover, a new algorithm to forecast the joint positions based on the polynomial fitting and improved Kalman filtering algorithms has been proposed, not only for limiting the region of matching, but also for marker occlusion and various maneuverability of the limb. Two methods are also applied to detect mismatch for ensuring a reliable tracking. Once 2D markers positions are collected, kinematic characteristics of the motion can be derived. Finally, the experimental results of the tracking system are presented. © 2010 IEEE.

关键词： Motion analysis

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Robust segmentation and volumetric registration in a multi-view 3D freehand ultrasound reconstruction system

Robust segmentation and volumetric registration in a multi-v...

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40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06

作者： Yu, Honggang Pattichis, Marios S. Goens, M. Beth Image and Video Processing and Communications Lab. Department of Electrical and Computer Engineering University of New Mexico Albuquerque NM 87131 United States Pediatric Cardiology Clinic University of New Mexico Children's Hospital Albuquerque NM 87131 United States

ISBN: (纸本)1424407850

In this paper, we present a new reconstruction method with volumetric registration and semi-automatic segmentation in a multi-view 3D freehand ultrasound imaging system. The new volumetric registration approach is performed on binarized walls using non-linear least squares. It can provide accurate multi-view reconstructions despite significant rigid target motion between different acoustic window acquisitions. A hybrid adaptive gradient vector flow (GVF) geometric active contour (GAC) model is used for image sequence segmentation. It allows for relatively simple initialization of the deformable model, while avoiding edge leaking at poor edges and small boundary gaps. The algorithms were validated on four ultrasound phantom data sets (eight sequences of a total of 336 images) and two echocardiography data sets (four sequences for a total of 75 images). Quantitative evaluation shows that automatic segmentation is comparable with manual segmentation. Using breath-holding and cardiac gating, volume estimates from multiview reconstructions of the left-ventricle were found to be in better agreement with clinical estimates than volumes estimated from single view reconstructions.

关键词： Echocardiography

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An Improved Outdoor Camera Calibration Method Based On EKF

An Improved Outdoor Camera Calibration Method Based On EKF

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2014 International Conference on Computer,communications and Information Technology(CCIT 2014)

作者： Shaopo Zhu Dong Hu Education Ministry's Key Lab of Broadband Wireless Communication and Sensor Network Technology Jiangsu Province's Key Lab of Image Procession and Image Communications Nanjing University of Posts and Telecommunications

ISBN: (纸本)9781629939865

An improved outdoor camera calibration method based on Extended Kalman Filter(EKF) is proposed in this paper. GPS coordinate system is introduced to establish world coordinate system in the calibration procedure. According to the characteristics of GPS coordinate converted to plane coordinate and the camera calibration model, we establish the mapping relations of reference points between image plane coordinate and the world coordinate. Further, we consider the world coordinate error, set the world coordinates as the measure quantities, use the method of EKF to get the optimal estimation of intrinsic and extrinsic camera parameters, in EKF the camera's intrinsic and extrinsic parameters are set as state variables, the transformation equations of image coordinate to the world coordinate are set as the measurement equations, and we let the observed feature points' image coordinates and corresponding world coordinates as the input of the filter. Experimental results confirmed that the proposed method with high precision.

关键词： camera calibration,GPS coordinate,EKF,world coordinate error

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Electroencephalogram Signal Analysis Based on the Improved k-nearest Neighbor Network

Electroencephalogram Signal Analysis Based on the Improved k...

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International Congress on image and Signal processing, BioMedical Engineering and Informatics

作者： Xian Yu Chengcheng Liu Jun Wang Jiafei Dai Jin Li Fengzhen Hou Image Processing and Image Communications Key Lab Nanjing University of Posts and Telecommunications Nanjing General Hospital of Nanjing Military Command College of Physics and Information Technology Shaanxi Normal University School of Science China Pharmaceutical University

ISBN: (纸本)9781509037117

In this paper, we propose a method to analyze epileptic electroencephalogram based on time series that is transformed from improved k-nearest neighbor network. The study of complex networks has become a hot research of electroencephalogram signal. Electroencephalogram time series generated by the network keeps node information of network, so researching the time series from the network can also achieve the purpose of studying epileptic electroencephalogram. The results of this experiment show that studying power spectrum of time series from the network is more easily than the power spectrum of time series directly generated from brain data to distinguish between normal and epileptic patients. In addition, studying the clustering coefficient of improved k-nearest neighbor network is also able to distinguish between normal and patients with epilepsy. This study can provide an important reference for the study of epilepsy and clinical diagnosis.

关键词： analysis of electroencephalogram signals improved k-nearest neighbor network time series epilepsy

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