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Multi-scale local features based on anisotropic heat diffusion and global eigen-structure

中国科学：信息科学（英文版） 2013年第11期56卷 53-62页

作者： LI Shuai QIN Hong HAO AiMin State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191 China School of Biological Science and Medical Engineering Beihang UniversityBeijing 100191 China Department of Computer Science State University of New York at Stony BrookStony Brook NY 11794-4400 USA State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191 China

Multi-scale local feature detection enables downstream registration and recognition tasks in medical image analysis. This paper articulates a novel robust method for multi-scale local feature extraction on volumetric data. The central idea is the elegant unification of local/global eigen-structures within the powerful framework of anisotropic heat diffusion. First, the local vector field is constructed by way of Hessian matrix and its eigenvectors/eigenvalues. Second, anisotropic heat kernels are computed using the vector field’s global graph Laplacian. Robust local features are manifested as extrema across multiple time scales, serving as volumetric heat kernel signature. To tackle the computational challenge for massive volumetric data, we propose a multiresolution strategy for hierarchical feature extraction based on our feature-preserving down-sampling approach. As a result, heat kernels and local feature identification can be approximated at a coarser level first, and then are pinpointed in a localized region at a finer resolution. Another novelty of this work lies at the initial heat design directly using local eigenvalue for anisotropic heat diffusion across the volumetric domain. We conduct experiments on various medical datasets, and draw comparisons with 3D SIFT method. The diffusion property of our local features, which can be interpreted as random walks in statistics, makes our method robust to noise, and gives rise to intrinsic multi-scale characteristics.

关键词： volumetric heat kernel anisotropic diffusion multi-scale local feature local/global eigen-structure volumetric image

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Salient object detection: A survey

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Computational Visual Media 2019年第2期5卷 117-150页

作者： Ali Borji Ming-Ming Cheng Qibin Hou Huaizu Jiang Jia Li MarkableAI New YorkUSA TKLNDST College of Computer ScienceNankai UniversityTianjinChina University of Massachusetts Amherst AmherstMAUSA State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijingChina

Detecting and segmenting salient objects from natural scenes, often referred to as salient object detection, has attracted great interest in computer vision. While many models have been proposed and several applications have emerged, a deep understanding of achievements and issues remains lacking. We aim to provide a comprehensive review of recent progress in salient object detection and situate this field among other closely related areas such as generic scene segmentation, object proposal generation, and saliency for fixation prediction. Covering 228 publications, we survey i) roots, key concepts, and tasks, ii) core techniques and main modeling trends, and iii) datasets and evaluation metrics for salient object detection. We also discuss open problems such as evaluation metrics and dataset bias in model performance, and suggest future research directions.

关键词： salient object detection saliency visual attention regions of interest

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Electrical engineering hall of fame: Reginald A. Fessenden

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PROCEEDINGS OF THE IEEE 2004年第11期92卷 1866-1869页

作者： Brittain, JE School of Computer and Information Technology Northeast Petroleum University DaQing China State Key Laboratory of Virtual Reality Technology and Systems BeiHang University Beijing China

Presents a biography of Fessenden and his contribution to radio broadcasting and science, during the period from the late 1870s up to his death in 1932.

关键词： Detectors Laboratories Testing Engineering profession Educational institutions Medals Radio broadcasting Underwater communication Underwater tracking Alternators

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Research on Crowdsourcing Price Game Model in Crowd Sensing

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computers, Materials & Continua 2021年第8期68卷 1769-1784页

作者： Weijin Jiang Xiaoliang Liu Dejia Shi Junpeng Chen Yongxia Sun Liang Guo School of Computer Science and Technology Hunan University of Technology and BusinessChangsha410205China Key Laboratory of Hunan Province for New Retail Virtual Reality Technology Changsha410205China School of Bioinformatics University of MinnesotaTwin Cities15213USA

Crowd-Sensing is an innovative data acquisition method that combines the perception of mobile devices with the idea of *** is a new application mode under the development of the Internet of *** perceptual data that mobile users can provide is *** crowdsourcing parties will share this limited data,but the cost that the crowdsourcing party can pay is limited,and enough mobile users are needed to complete the perceptual task,making the group wisdom is really *** this process,there is bound to be a game between the crowds and the mobile *** of the existing researches consider a group-aware system.A group of mobile users will directly share or compete for the opportunity of the crowd-holders to do tasks and get paid,the behavior of multiple crowd-source parties,and their bilateral interaction with mobile *** research is not clear enough and there is no targeted *** paper will model and analyze the dynamic evolution process of crowd sensing *** on the unique characteristics of crowd-source non-cooperative game and crowd-sourced Nash equilibrium,we will develop a perceptual plan for mobile users and use the stability analysis of iterative algorithms to explore a way to better match the capabilities of mobile users and the needs of crowdsourced *** theoretical analysis and simulation results verify the dynamic evolution model of crowdsourcing in group perception and propose a method to improve the efficiency of crowdsourcing.

关键词： Crowd-sensing crowdsourcing incentives sensor networks

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A MAC protocol for congested cognitive radio network

A MAC protocol for congested cognitive radio network

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2nd International Conference on Intelligent Networks and Intelligent Systems, ICINIS 2009

作者： Yue, Song-Song Wu, Wei State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science Beihang University Beijing China

ISBN: (纸本)9780769538525

This paper proposed a media access control (MAC) protocol for distributed cognitive radio network, which can work effectively in congested network by dynamic spectrum allocation. Cognitive nodes user chose the communication channel by negotiation, considering the channel usage of neighbours. The scheme can reduce the interference between nodes by selecting proper channel, improve the throughput of network significantly, especially when the network is highly congested. The simulation results show that our protocol outperforms the random allocation protocol by 48.2% in throughput. © 2009 IEEE.

关键词： Cognitive radio

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Unsupervised Martian Dust Storm Removal via Disentangled Representation Learning

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Research in Astronomy and Astrophysics 2022年第9期22卷 255-266页

作者： Dong Zhao Jia Li Hongyu Li Long Xu State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBejing 100191China State Key Laboratory of Space Weather National Space Science CenterChinese Academy of SciencesBeijing 100190China Peng Cheng Laboratory Shenzhen 518000China

Mars exploration has become a hot spot in recent years and is still advancing rapidly. However, Mars has massive dust storms that may cover many areas of the planet and last for weeks or even months. The local/global dust storms are so influential that they can significantly reduce visibility, and thereby the images captured by the cameras on the Mars rover are degraded severely. This work presents an unsupervised Martian dust storm removal network via disentangled representation learning(DRL). The core idea of the DRL framework is to use the content encoder and dust storm encoder to disentangle the degraded images into content features(on domain-invariant space) and dust storm features(on domain-specific space). The dust storm features carry the full dust storm-relevant prior knowledge from the dust storm images. The “cleaned” content features can be effectively decoded to generate more natural, faithful, clear *** primary advantages of this framework are twofold. First, it is among the first to perform unsupervised training in Martian dust storm removal with a single image, avoiding the synthetic data requirements. Second, the model can implicitly learn the dust storm-relevant prior knowledge from the real-world dust storm data sets, avoiding the design of the complicated handcrafted priors. Extensive experiments demonstrate the DRL framework’s effectiveness and show the promising performance of our network for Martian dust storm removal.

关键词： planets and satellites:atmospheres planets and satellites:general planets and satellites:surfaces

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Shadow obstacle model for realistic corner-turning behavior in crowd simulation

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Frontiers of Information technology & Electronic Engineering 2016年第3期17卷 200-211页

作者： Gao-qi HE Yi JIN Qi CHEN Zhen LIU Wen-hui YUE Xing-jian LU Department of Computer Science and Engineering East China University of Science and Technology Shanghai 200237 China MOE Key Laboratory of Geographic Information Science East China Normal University Shanghai 200241 China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing 100191 China College of Information Science and Technology Ningbo University Ningbo 315211 China

This paper describes a novel model known as the shadow obstacle model to generate a realistic comer-tuming behavior in crowd simulation. The motivation for this model comes from the observation that people tend to choose a safer route rather than a shorter one when turning a comer. To calculate a safer route, an optimization method is proposed to generate the corner-turning rule that maximizes the viewing range for the agents. By combining psychological and physical forces together, a full crowd simulation framework is established to provide a more realistic crowd simulation. We demonstrate that our model produces a more realistic comer-turning behavior by comparison with real data obtained from the experiments. Finally, we per- form parameter analysis to show the believability of our model through a series of experiments.

关键词： Comer-turning behavior Crowd simulation Safety awareness Rule-based model

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A Novel Divide and Conquer Solution for Long-term Video Salient Object Detection

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Machine Intelligence Research 2024年第4期21卷 684-703页

作者： Yun-Xiao Li Cheng-Li-Zhao Chen Shuai Li Ai-Min Hao Hong Qin State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191China College of Computer Science and Technology China University of Petroleum(East China)Qingdao 266580China Department of Computer Science Stony Brook UniversityNew York 11794USA

Recently,a new research trend in our video salient object detection(VSOD)research community has focused on enhancing the detection results via model self-fine-tuning using sparsely mined high-quality keyframes from the given *** such a learning scheme is generally effective,it has a critical limitation,i.e.,the model learned on sparse frames only possesses weak generalization *** situation could become worse on“long”videos since they tend to have intensive scene ***,in such videos,the keyframe information from a longer time span is less relevant to the previous,which could also cause learning conflict and deteriorate the model ***,the learning scheme is usually incapable of handling complex pattern *** solve this problem,we propose a divide-and-conquer framework,which can convert a complex problem domain into multiple simple ***,we devise a novel background consistency analysis(BCA)which effectively divides the mined frames into disjoint *** for each group,we assign an individual deep model on it to capture its key attribute during the fine-tuning *** the testing phase,we design a model-matching strategy,which could dynamically select the best-matched model from those fine-tuned ones to handle the given testing *** experiments show that our method can adapt severe background appearance variation coupling with object movement and obtain robust saliency detection compared with the previous scheme and the state-of-the-art methods.

关键词： Video salient object detection background consistency analysis weakly supervised learning long-term information background shift.

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A robust approach for long-term hand tracking 12

A robust approach for long-term hand tracking

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12th International Bhurban Conference on Applied Sciences and technology, IBCAST 2015

作者： Abdul Aziz, Muhammad Ali Niu, Jianwei Zhao, Xiaoke State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science Beihang University Beijing China

ISBN: (纸本)9781479963690

Considerable challenges arise in hand tracking due to background clutter, inconsistent lighting, scale changes, occlusions and total object disappearance. In order to cope with these difficulties, we present a robust hand tracker based on enhanced particle filters. To overcome the inherent shortcomings of the particle filter approach, we infuse it with the mean shift (CAMSHIFT) method, thereby reducing the number of the particles and improving their quality. Furthermore, by using detection based on the αHOG (Alpha Histograms of Oriented Gradients) feature proposed in our earlier work [1], our tracker ensures that the hand is re-tracked if it disappears from the image frame and re-enters it. We base our appearance model on RGB color histograms and our newly proposed RLBP (Rotation Invariant Noise Compensated Local Binary Patterns) descriptor, which is an improved version of the LBP (Local Binary Patterns) descriptor. By virtue of our experiments, we show that our proposed tracker shows excellent results in comparison to state-of-the-art trackers on various challenging hand sequences collected by us as well as benchmark object sequences generally used in object tracking. Moreover, our tracker shows strong reacquisition ability, something that the existing hand trackers are not equipped with. © 2015 IEEE.

关键词： Local binary pattern

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Locomotion perception and redirection

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virtual Reality & Intelligent Hardware 2021年第6期3卷 I0003-I0004页

作者： Miao WANG Songhai ZHANG Shimin HU State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China

Locomotion is a fundamental interaction technique that allows free navigation in virtual scenes.A large body of literature has demonstrated that natural locomotion experience can significantly improve the sense of presence and help users achieve better performance in tasks such as searching and *** the upcoming metaverse era,locomotion will play a critical role in the success of large-scale interactive *** and redirection are two tightly connected problems in virtual *** a limited physical condition and a target virtual scene,how to make the perceived locomotion as natural as possible,and further unknowingly redirect the user in the physical world is an open *** this special issue,we have selected five papers that provide their latest updates for research problems of view control,virtual jumping,climbing,and searching.

关键词： redirect interactive motion

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