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Portrait image segmentation based on improved grabcut algorithm 6th

Portrait image segmentation based on improved grabcut algori...

6th International Conference on Swarm Intelligence, ICSI 2015 held in conjunction with the 2nd BRICS Congress on Computational Intelligence, CCI 2015

作者： Li, Shuai Zheng, Xiaohui Chen, Xianjun Zhan, Yongsong Key Laboratory of Cloud Computing and Complex System Guilin University of Electronic Technology Guilin Guangxi541004 China Guangxi Experiment Center of Information Science Guilin University of Electronic Technology Guilin Guangxi541004 China Key Laboratory of Intelligent Processing of Computer Image and Graphics Guilin University of Electronic Technology Guilin Guangxi541004 China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin Guangxi541004 China Information Engineering School Haikou College of Economics Haikou Hainan571127

ISBN: (纸本)9783319204680

Traditional computer portrait caricature system mainly take the method that exaggerate and deform real images directly, that lead the facial image background also been deformed when exaggerate facial image. If in pretreatment stage, we segmented the characters and background of the input image, and then do the subsequent processing, the problem may be solved. But for better portrait caricature effects, we need an excellent segmentation algorithm. So, we propose an improved Grabcut image segmentation algorithm and use it to extract the prospect character image for exaggeration and deformation. In practical application, we separate deform and exaggerate the foreground characters image with TPS method, then fuse it with the original or new background picture, get the final image. Application proves, the method solves the background deformation problem well, and improves the quality and rate of image segmentation, caricature synthesis effect reality and natural. © Springer International Publishing Switzerland 2015.

关键词： Image segmentation

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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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When smart grid meets geo-distributed cloud: An auction approach to datacenter demand response

When smart grid meets geo-distributed cloud: An auction appr...

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IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： Zhi Zhou Fangming Liu Zongpeng Li Hai Jin Key Laboratory of Services Computing Technology and System Huazhong University of Science and Technology China Department of Computer Science University of Calgary Canada

Datacenter demand response is envisioned as a promising tool for mitigating operational stability issues faced by smart grids. It enables significant potentials in peak load reduction and facilitates the incorporation of distributed generation. Monetary refund from the smart grid can also alleviate the cloud's burden in escalating electricity cost. However, the current demand response paradigm is inefficient towards incentivizing a cloud that runs over geo-distributed datacenters. Leveraging auction theory, this work presents an efficient incentive mechanism to elicit demand response from geo-distributed clouds. To determine the winning bids and their corresponding payments, the cloud that acts as the auctioneer needs to solve a set of winner determination problems that are highly challenging. By integrating techniques from the Gibbs sampling method and the alternating direction method of multipliers, we propose a decentralized algorithm for each datacenter to make autonomous decisions on winning bid selection and workload management, striking a balance among the economic efficiency, truthfulness and the computational efficiency. Through extensive trace-driven evaluations, we demonstrate that our incentive mechanism constitutes a win-win mechanism for both the geo-distributed cloud and the smart grid.

关键词： Smart grids Load management Power demand Servers Cost accounting Conferences Computers

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Survey on the search of Internet of Things

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Tongxin Xuebao/Journal on Communications 2015年第12期36卷 57-76页

作者： Gao, Yun-Quan Li, Xiao-Yong Fang, Bin-Xing Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education Beijing University of Posts and Telecommunications Beijing100876 China School of Computer Science and Technology Anhui University of Technology Ma'anshan243032 China

With the popularization and development of the Internet of Things, the search of Internet of Things urgently needs to be solved in academia and industry and becomes a hot research topic. With the increasing data generated by sensors, only the search of IoT makes this data valuable. However, different from the traditional Internet search engines (such as Baidu, Google, Bing, Yahoo, etc), the search of IoT has different search objects and search architecture and data in the Internet of Things are massive, real-time, highly dynamic, heterogeneous, highly insecure. The above characteristics make search of IoT face more challenges. Firstly, the concept, characteristics, related technologies of search of IoT were summarized and presented. Secondly, several typical systems and related algorithms were described in detail. Finally, the current problems, the challenges and research prospects of this field for future were presented. © 2015, Editorial Board of Journal on Communications. All right reserved.

关键词： Surveys

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New service discovery algorithm based on DHT for mobile application

New service discovery algorithm based on DHT for mobile appl...

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IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks (SECON)

作者： De-gan Zhang Wen-bin Li Zhen Ma Key Laboratory of Computer Vision and System Ministry of Education China Tianiin Key Lab of Intelligent Computing & Novel software Technology Tianjin University of Technology China

In order to solve how to enhance the discovery efficiency and coverage, based on DHT (Distributed Hash Table), we put forward a new algorithm of service discovery for mobile application. In traditional DHT discovery algorithm, each node maintains the finger-table that store node information of adjacent node. By using Small-World Theory, we put forward adding a remote node into the finger-table and adding the corresponding remote index. It is different from selecting the remote connection node randomly. We select the remote connection node by calculating local node and it can assure not only the cove range of service discovery but also not increase the length of finger-table, which simplifies the calculation of the finger-table and maintenance work. The simulation proved that the algorithm can reduce the path length of service discovery effectively, improve success rate of service discovery.

关键词： Fingers Peer-to-peer computing Algorithm design and analysis Redundancy Servers Mobile applications Conferences

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A Distributed Link Prediction Algorithm Based on Clustering in Dynamic Social Networks

A Distributed Link Prediction Algorithm Based on Clustering ...

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IEEE International Conference on systems, Man and Cybernetics

作者： Han Yuan Yunlong Ma Feng Zhang Min Liu Weiming Shen Tongji University School of Electronic and Information Engineering Shanghai China Tongji University The Key Laboratory of Embedded System and Service Computing Shanghai China

ISBN: (纸本)9781479986989

Link prediction in network attempts to predict the exist-yet-unknown links or future links in accordance with the node properties and the network typology. It has been used in many domains such as social network, biology experiment, and criminal investigations. Classical methods are based on graph topology structure and path features but few consider clustering information. Actually, clustering information plays an important role in link prediction, it connects the sparse nodes and other communities to form intensive communities. Besides the application of clustering, the MapReduce-based method is used to improve the efficiency. The validity of algorithm is verified by real-world datasets. The experimental results show that the proposed algorithm has a higher prediction accuracy and lower time complexity, and is more scalable than traditional methods executed by a single machine.

关键词： Prediction algorithms Clustering algorithms Indexes Prediction methods Algorithm design and analysis Heuristic algorithms Social network services

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A Stable and Distributed Community Detection Algorithm Based on Maximal Cliques

A Stable and Distributed Community Detection Algorithm Based...

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IEEE International Conference on systems, Man and Cybernetics

作者： Feng Gui Yunlong Ma Feng Zhang Min Liu Rong Yin Weiming Shen Tongji University School of Electronic and Information Engineering Shanghai China Tongji University The Key Laboratory of Embedded System and Service Computing Shanghai China

ISBN: (纸本)9781479986989

In the research area of community detection which aims at detecting some highly cohesive vertex subsets in social network, there mainly exist some problems, such as the algorithms with comparatively excellent quality of the final partitioning usually have high time complexity and some other fast algorithms often result in low quality of partitioning or other disadvantages. Nowadays, the increasing demands for community detection in large-scale social networks necessitate the use of distributed and scalable methods to detect communities in an effective and efficient manner. Label propagation algorithm (LPA), whose time complexity is O (m) on a network with m edges, is a near linear time algorithm to detect community effectively. Besides, owing to having good scalability, the parallel version of LPA (DLPA) is suitable for community detection in large-scale social networks. However, DLPA synchronously updates the vertices labels, which usually brings about label oscillations and results in low quality of partitioning. In this paper, we analyze the drawbacks of DLPA and propose a novel method C-DLPA, which combines DLPA with the notion of maximal cliques and at the same time utilizes a new updating mechanism that updating each node' label by probability of its adjacent nodes, to make final partitioning become more accurate and to avoid oscillations effectively. The experimental results show that C-DLPA has better performance is not only low time cost by as much to avoid oscillations but its community detection accuracy compared with DLPA.

关键词： Oscillators Image edge detection Time complexity Partitioning algorithms Algorithm design and analysis Social network services Transforms

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An efficient algorithm of information recommendation between groups in social networks

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Tien Tzu Hsueh Pao/Acta Electronica Sinica 2015年第6期43卷 1090-1093页

作者： Huang, Zhen-Hua Zhang, Bo Fang, Qiang Xiang, Yang Department of Computer and Technology Tongji University Shanghai201804 China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai201804 China College of Information Mechanical and Electrical Engineering Shanghai Normal University Shanghai200234 China

Information recommendation between groups is one of the most important ways for information sharing and transmitting in social networks. However, it needs exponential time cost to achieve the exact optimal recommendation solution. Hence this paper proposed an efficient algorithm EAOORS (Efficient Algorithm for Obtaining Optimal Recommendation Solution) which equivalently reduced this exponential time cost problem to extended steiner tree problem, and fast achieved the approximate optimal recommendation solution in the polynomial time complexity. The experimental result shows that the EAOORS algorithm is more efficient than the existing ones. ©, 2015, Chinese Institute of Electronics. All right reserved.

关键词： Approximation algorithms

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Load Balancing for Parallel Discrete Event Simulation of Stochastic Reaction and Diffusion

Load Balancing for Parallel Discrete Event Simulation of Sto...

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IEEE International Conference on Smart City

作者： Zhongwei Lin Yiping Yao State Key Laboratory of High Performance Computing National University of Defense Technology College of Information System and Management National University of Defense Technology

ISBN: (纸本)9781509018949

Load balancing plays an essential role in parallel and distributed computing. In this paper, we present the load balancing issue of our multi-threaded parallel discrete event simulator for stochastic simulation and our solution. The computational and communicational workload of each thread is assessed during simulation, and the state of the simulation is represented by this assessment. We utilize a multi-state Q-learning approach to determine the parameters of workload migration-the type of objective workload, the number of threads involved in migration and the load to be exchanged. Workload is transferred within the same process by mapping it to the new thread directly and by communication between processes. As the test on a calcium wave model shows, our solution achieved 31% improvement in execution time by migrating workload among threads within the same process, 21% improvement when workload is transferred within the same node, and 16% when remote communication is used.

关键词： Load balancing Multiple thread Performance Parallel stochastic simulation

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Greedy approach based heuristics for partitioning SpMxV on FPGAs

Greedy approach based heuristics for partitioning SpMxV on F...

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International Conference on Field Programmable Logic and Applications

作者： Jiasen Huang Weina Lu Junyan Ren State Key Laboratory of ASIC and System Fudan University Shanghai China Institute of Computing Technology Chinese Academy of Sciences China

To eliminate the overhead of zero padding in sparse matrix-vector multiplication (SpMxV), prior works have been focusing on partitioning a sparse matrix into row vectors sets (RVS's) or sub-matrices. Nevertheless, performance degraded still due to the sparsity pattern of a sparse matrix. In this paper, we propose a heuristics, called recursive merging, which uses greedy approach to recursively merge those row vectors of nonzeros in a matrix into the RVS's, such that each set included is ensured a local optimal solution. For ten uneven benchmark matrices from the University of Florida Sparse Matrix Collection, our proposed partitioning algorithm is always identified as the method with the highest mean density (over 96%). An average speedup of 249X is thus achieved for all these ten matrices when 32 processors are allocated for implementation SpMxV on XC7V485T FPGAs.

关键词： Sparse matrices

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