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Author Correction: The challenge of mapping the human connectome based on diffusion tractography

Nature communications 2019年第1期10卷 5059页

作者： Klaus H Maier-Hein Peter F Neher Jean-Christophe Houde Marc-Alexandre Côté Eleftherios Garyfallidis Jidan Zhong Maxime Chamberland Fang-Cheng Yeh Ying-Chia Lin Qing Ji Wilburn E Reddick John O Glass David Qixiang Chen Yuanjing Feng Chengfeng Gao Ye Wu Jieyan Ma Renjie He Qiang Li Carl-Fredrik Westin Samuel Deslauriers-Gauthier J Omar Ocegueda González Michael Paquette Samuel St-Jean Gabriel Girard François Rheault Jasmeen Sidhu Chantal M W Tax Fenghua Guo Hamed Y Mesri Szabolcs Dávid Martijn Froeling Anneriet M Heemskerk Alexander Leemans Arnaud Boré Basile Pinsard Christophe Bedetti Matthieu Desrosiers Simona Brambati Julien Doyon Alessia Sarica Roberta Vasta Antonio Cerasa Aldo Quattrone Jason Yeatman Ali R Khan Wes Hodges Simon Alexander David Romascano Muhamed Barakovic Anna Auría Oscar Esteban Alia Lemkaddem Jean-Philippe Thiran H Ertan Cetingul Benjamin L Odry Boris Mailhe Mariappan S Nadar Fabrizio Pizzagalli Gautam Prasad Julio E Villalon-Reina Justin Galvis Paul M Thompson Francisco De Santiago Requejo Pedro Luque Laguna Luis Miguel Lacerda Rachel Barrett Flavio Dell'Acqua Marco Catani Laurent Petit Emmanuel Caruyer Alessandro Daducci Tim B Dyrby Tim Holland-Letz Claus C Hilgetag Bram Stieltjes Maxime Descoteaux Division of Medical Image Computing German Cancer Research Center (DKFZ) Heidelberg 69120 Germany. k.maier-hein@dkfz.de. Division of Medical Image Computing German Cancer Research Center (DKFZ) Heidelberg 69120 Germany. Sherbrooke Connectivity Imaging Lab (SCIL) Université de Sherbrooke Sherbrooke QC J1K 0A5 QC Canada. Department of Intelligent Systems Engineering School of Informatics and Computing Indiana University Bloomington IN 47408 USA. Krembil Research Institute University Health Network Toronto Canada M5G 2C4. Department of Neurological Surgery University of Pittsburgh School of Medicine Pittsburgh PA 15213 USA. IMT-Institute for Advanced Studies Lucca 55100 Italy. Department of Diagnostic Imaging St. Jude Children's Research Hospital Memphis TN 38105 USA. University of Toronto Institute of Medical Science Toronto Canada M5S 1A8. Institute of Information Processing and Automation Zhejiang University of Technology Hangzhou 310023 Zhejiang China. United Imaging Healthcare Co Shanghai 201807 China. Shanghai Advanced Research Institute Shanghai 201210 China. Laboratory of Mathematics in Imaging Harvard Medical School Boston MA 02215 USA. Center for Research in Mathematics Guanajuato 36023 Mexico. PROVIDI Lab Image Sciences Institute University Medical Center Utrecht Utrecht 3508 The Netherlands. Cardiff University Brain Research Imaging Centre School of Psychology Cardiff University Maindy Road Cardiff CF24 4HQ UK. Department of Radiology University Medical Center Utrecht Utrecht 3508 The Netherlands. Centre de recherche institut universitaire de geriatrie de Montreal (CRIUGM) Université de Montréal Montreal QC Canada H3W 1W5. Sorbonne Universités UPMC Univ Paris 06 CNRS INSERM Laboratoire d'Imagerie Biomédicale (LIB) 75013 Paris France. Center for Advanced Research in Sleep Medicine Hôpital du Sacré-Coeur de Montréal Montreal Canada H4J 1C5. Neuroimaging Unit Institute of Bioimaging and Molecular Physiology (IBFM) Nat

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Online Pedestrian Tracking Using Ensemble Color Feature

Online Pedestrian Tracking Using Ensemble Color Feature

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International Conference on Computer and Information Technology (CIT)

作者： Bo Zhang Yi Xu Xiaokang Yang Department of Electronic Engineering Shanghai Jiao Tong University Cooperative Medianet Innovation Center Shanghai Key Laboratory of Digital Media Processing and Transmissions Institute of Image Communication and Network Engineering Shanghai China

In this paper, we propose a novel online visual tracking algorithm using ensemble color feature. Visual tracking has long been one of the most important topics in computer vision. In recent years, significant progress has been achieved by the state-of-the-art tracking algorithms. However, some challenging problems still remain unsolved. One general problem is that it is difficult for a tracking algorithm to achieve both high accuracy and efficiency. More specifically, most tracking algorithms base on the hypothesis that the tracking object is a rigid body. Thus, some visual features are disabled when the hypothesis is invalid. Meanwhile, the existing trackers tend to fail when the target object changes poses, because such changes lead to the dramatic mismatch between the momentaneous appearance model and the learned one. The last problem is especially serious when the tracking targets are pedestrians, which suffer irregular pose and shape changes while they walk or run. The proposed algorithm applies ensemble color feature model. It takes pedestrians' physiological structure into consideration, and takes advantage of color histogram information under several color spaces, including the RGB, normRGB, HSV, and Lab. Since histogram is a statistic-based feature, and the garments of pedestrians provide abundant color information, our appearance model using ensemble color feature is more robust to pose and shape changes. Experiments on Caltech Pedestrian Database with evaluation of the state-of-the-art algorithms show better performance of the proposed algorithm.

关键词： Color image color analysis Target tracking Visualization Algorithm design and analysis Histograms Shape

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Visual comfort assessment of stereoscopic images with multiple salient objects

Visual comfort assessment of stereoscopic images with multip...

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IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)

作者： Xiaonan Zhang Jun Zhou Jianyu Chen Xiaoqiang Guo Ya Zhang Xiao Gu Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai China Institute of Image Communication and Network Engineering Shanghai Jiao Tong University Shanghai China Academy of Broadcasting Science Beijing China

This paper focuses on discomfort assessment issue for S3D images with multiple salient objects, and proposes four kinds of visual features of S3D images that have potential correlations with visual discomfort, including disparity distribution features, disparity jump features, object distribution features as well as object width features. A stereoscopic image database is designed focusing on multiple salient object scenarios and prediction model is built using support vector regression based on the proposed features. Prediction performance evaluation result shows that the proper combinations of the proposed features can achieve effective visual discomfort prediction for these types of pictures, and also shows that the convergence adjustments induced by the disparity discrepancies among the salient objects do cause visual discomfort in these scenarios.

关键词： Visualization Stereo image processing Feature extraction Three-dimensional displays image databases Convergence

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A new approach to create 3D fixation density maps for stereoscopic images

A new approach to create 3D fixation density maps for stereo...

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3DTV Conference

作者： Baoyan Ma Jun Zhou Xiao Gu Mingmin Wang Ya Zhang Xiaoqiang Guo Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai China Institute of Image Communication and Network Engineering Shanghai Jiao Tong University Shanghai NGB laboratories Co. LTD Shanghai China Academy of Broadcasting Science Beijing China

An approach to create fixation density maps(FDM) for stereoscopic images is proposed in this paper, overcoming the shortages of current methods. A new representation of stereoscopic images like Computed Tomography (CT) is used, which can show more information such as depth and discomfort zone. Apart from this, we follow the protogenetic 2D calibration of eyetracker by a 3D offline calibration to gain accuracy of 3D gaze points, tuned to a particular user. We combine these two parts through classifying eyetracking data to several depth planes which are segmented in the procedure of the representation method like CT, and obtain the fixation distribution in different depth levels for a stereoscopic image.

关键词： Three-dimensional displays Stereo image processing Calibration Frequency division multiplexing image segmentation Visualization Accuracy

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A depth map estimation approach for trinocular stereo

A depth map estimation approach for trinocular stereo

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IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)

作者： Jun Zhou Ling Wang Xiao Gu Kang Xu Ya Zhang Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai China Institute of Image Communication and Network Engineering Shanghai Jiao Tong University Shanghai China Shanghai Media and Entertainment Technology Group Co. Ltd. Shanghai China

This paper presents an approach for dense depth estimation taking the input of a trinocular stereo. The approach works with a global energy minimization framework based on Markov Random Field models. The occlusion and spatial consistency constraints are explicitly considered in an iterative fashion. Depth maps are initialized by belief propagation using AD-Census metric, and then refined by Mean Shift Segments Fusion. We further incorporate the occlusion constraint for trinocular stereo to refine our depth map. In order to make the inference tractable, we implement our algorithm in an iterative scheme where the disparity map and occlusion map of each view are updated iteratively. Finally, three disparity maps corresponding to a trinocular stereo are estimated. Our approach addresses the problems such as untextured regions, occlusions, inconsistency in spatial region in a unified framework. The experimental results show our approach works well on trinocular stereo.

关键词： Silicon Integrated circuits image color analysis image segmentation Estimation Belief propagation Three-dimensional displays

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The 5th International Conference on Biomedical engineering and Biotechnology (ICBEB 2016) Abstracts

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BMC MEDICAL IMAGING 2016年第SUPPL 1期16卷 65-65页

作者： [Anonymous] Department of MRI Shandong Medical Imaging Research Institute Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China Department of Interventional Radiology Shandong Provincial Hospital Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China College of Information Science and Technology Engr. Research Center of Digitized Textile & Fashion Tech. for Ministry of Education Donghua University Shanghai 201620 China Intelligent multimedia information processing Lab College of Software Northeastern University Shenyang Liaoning Province 110004 China Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China School of Computer Science and Technology Nanjing Normal University Nanjing China Department of Electrical Engineering The City College of New York CUNY New York USA Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing Nanjing China School of Electronic Science and Engineering Nanjing University Nanjing Jiangsu 210046 China College of Engineering Nanyang Technological University Singapore 639798 Singapore School of Electronic Information Shanghai Dianji University Shanghai China School of Natural Sciences and Mathematics Shepherd University Shepherdstown WV 25443 USA Davis College of Agriculture Natural Resources and Design West Virginia University Morgantown WV 26505 USA State Key Laboratory of Millimeter Waves Southeast University Nanjing 210096 China Center of Medical Physics and Technology Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China College of Agricultural and Life Sciences University of Florida Gainesville FL 32611 USA Courant Institute of Mathematical Sciences New York University New York NY 10012 USA Translational Imaging Division & MRI Unit Columbia University and New York State Psychiatric Institute New York NY 10032 USA Guangxi Key Laboratory of Manufacturing System & Adv

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A QoE friendly rate adaptation method for DASH

A QoE friendly rate adaptation method for DASH

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IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)

作者： Yuming Cao Xiaoquan You Jia Wang Li Song Institute of Image Communication and Network Engineering Shanghai Jiao Tong University Shanghai Key Laboratory of Multi Media Processing and Transmissions Shanghai

MPEG-DASH introduced open standards into HTTP streaming, which was a huge step forward. The scope of the MPEG-DASH standard was limited to the Media Presentation Description (MPD) format of the manifest files as well as the segmentation standards for the server, but did not include the client application as part of their standards. Particularly a good representation switching algorithm at DASH client should adapt to time varying bandwidth with better QoE (Quality of Experience). In this paper, we propose a QoE friendly rate adaptation method which can achieve less switching times and more gradual quality change. To achieve these purposes, we propose a fixed-interval buffer model, which keeps the representation level unchanged whenever the media buffer size is within the preset interval. We also design a step-wise switch-up method to prevent buffer overflow and a switch-down method based on intermediate quality level to prevent buffer underflow. A quick boot algorithm is introduced to fully improve the performance of the proposed scheme. Experimental results show that the proposed algorithm can achieve more satisfactory results compared with existing ones.

关键词： Bandwidth Bit rate Switches Heuristic algorithms Streaming media Standards Algorithm design and analysis

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Multilevel DCT-based zerotree image coding

Multilevel DCT-based zerotree image coding

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IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)

作者： Kankan Zheng Liang Zhang Rong Xie Institute of Image Communication and Network Engineering & Shanghai Key Laboratory of Digital Media Processing and Transmission Shanghai Jiao Tong University Shanghai China

image and video coding is fundamental to data storage and transmission. JPEG 2000 is the latest international image coding standard which exploits wavelet transform for image compression. Zerotree coding structure is an efficient algorithm for coding of wavelet transform coefficients. However, implementation complexity of wavelet transform and long coding process of zerotree structure may limit the application in some cases. In this paper, an idea of multilevel DCT-based zerotree image coding is proposed, in which Wavelet Transform (WT) is replaced by Discrete Cosine Transform (DCT) and DCT coefficients are regrouped into subbands of different frequencies. Furthermore, a new zerotree coding structure is proposed to reduce the complexity of zerotree coding process. A conventional zerotree with a parent-child relation of 2×2 offspring is expanded to the one of 4×4 offspring. Coefficients reorder and inverse DCT are needed when DCT transform size is not a power of 4. This expansion makes each parent node of zerotree coding structure have more child nodes and, therefore, reduce the complexity of encoding process. Simulation results of images with different spatial resolutions are presented to show the advantage of the proposed algorithm. The proposed multi-level DCT-based zerotree image coding algorithm performs similar coding performance as the SPIHT method. The zerotree coding structure with a parent-child relation of 4×4 pixels can significantly reduce the complexity of high-bitrate coding process without sacrificing image subjective quality.

关键词： Discrete cosine transforms image coding Encoding Spatial resolution Wavelet transforms Bit rate

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Spatial Error Concealment with Adaptive Linear Predictor

Spatial Error Concealment with Adaptive Linear Predictor

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IEEE International Symposium on Circuits and Systems

作者： Jing Liu Guangtao Zhai Xiaokang Yang Bing Yang Institute of Image Communication and Network Engineering Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai Jiaotong University Shanghai 200240 China

ISBN: (纸本)9781479934331

In this paper, we propose a novel spatial error concealment algorithm based on adaptive linear predictor. The predictor automatically tunes its order and support shape according to local contexts. The optimal order is determined using Bayesian Index Criterion (BIC). The order-adaptive predictor is able to recover more important features or structures. Simulation results show that compared to the state-of-the-art error concealment algorithms, the proposed method gives better reconstruction performance in terms of objective and subjective evaluations.

关键词： Data Security linear predictor Self tuning subjective evaluation Simulation results

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An improved compressive tracker for multiple pedestriansin surveillance videos

An improved compressive tracker for multiple pedestriansin s...

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International Conference on Audio, Language and image processing, ICALIP

作者： Zhengyan Ding Shibao Zheng Ming Xue Guang Tian Hongbo Li Wenjie Zhu Institute of Image Communication and Network Engineering Shanghai Jiao Tong University Shanghai China Shanghai Key Labs of Digital Media Processing and Communication Shanghai China Bocom smart network technologies Inc Shanghai China

ISBN: (纸本)9781479939046

This paper proposes an improved online framework based on Compressive Tracker (CT) for multiple pedestrian tracking in surveillance videos. The CT method proposed by Zhang et al was originally used for single object tracking, and fails to make use of context information during the tracking process. To overcome the crucial drawbacks of CT, our method implements multi-scale tracking and fuse CT with Kalman Filter to take advantage of the spatio-temporal context information. Additionally, incorporated with the detection of foreground blobs and an online learned detector, this paper introduces a supplementary mechanism to handle the inter-target occlusion. Experimental results on realistic sequences demonstrate the effectiveness of our approach.

关键词： Target tracking Computed tomography Feature extraction Surveillance image coding Detectors Object tracking

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