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Human action recognition: A novel application of the stochastic detector enriched by body-parts information

Journal of Information and Computational science 2011年第10期8卷 1873-1880页

作者： Ding, Jian Ye, Mao School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 611731 China State Key Lab. for Novel Software Technology Nanjing University Nanjing 210093 China

In this paper, we investigate the problem of human action recognition from the video. And a posetoaction hierarchical recognition step is adopted. Different from previous works which define some particular distances in the Euclidean space to measure the difference between any two human poses, we propose a new Probabilistic Pattern Distance (PPD). This measurement fully considers the ambiguity and the rich information contained in a human body. Then, Hidden Markov Model (HMM) will be used to recognize the human action. Final experimental results demonstrate that our model can effectively improve the action recognition performance, especially when a stable human silhouette image can not be obtained. © 2011 by Binary Information Press.

关键词： Hidden Markov models

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Content-based intelligent video recorder with its implementation on sports video 11

Content-based intelligent video recorder with its implementa...

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3rd International Conference on Internet Multimedia Computing and Service, ICIMCS 2011

作者： Jiang, Shuqiang Huang, Qingming Zhao, Zhao Key Lab. of Intell. Info. Process. Inst. of Comput. Tech. CAS Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100049 China Department of Computer Science Virginia Tech. United States

ISBN: (纸本)9781450309189

With the fast advances of integration of telecommunications networks, cable TV networks and the internet. TV video programs can be regarded as a special kind of internet information. This paper analyzes the users' requirements to the digital video recorder and proposes a three level framework for the Intelligent Video Recorder (IVR) based on the widely researched semantic video analysis and understanding technology. It provides intelligent playing, recording and browsing functions to the users which can help them personally record and deal with the TV programs. In addition, we explain how to achieve these functions via an implementation on sports videos. The IVR proposed in this paper can not only save the users' time but also provide them with various perspectives to videos in order to satisfy their personal requirements. IVR framework proposed in this paper gives a prototype of the future recorder design and the evaluations on sports videos demonstrate the rationality of this scheme. © 2011 ACM.

关键词： Sports

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Phoenix: Peer-to-peer location based notification in mobile networks

Phoenix: Peer-to-peer location based notification in mobile ...

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8th IEEE International Conference on Mobile Ad-hoc and Sensor Systems, MASS 2011

作者： Xiong, Yongping He, Wenbo Chen, Canfeng Ma, Jian Sun, Limin State Key Lab. of Networking and Switching Tech. Beijing Univ. of Posts and Telecomm. China Department of Computer Science University of New Mexico Albuquerque NM United States Nokia Research Center Beijing China Wuxi SensingNet Industrialization Research Institute Wuxi China Institute of Software Chinese Academy of Sciences Beijing China

ISBN: (纸本)9780769544694

Location Based Notification (LBN) aims to alert the users in a target area with the information of interest to them. With a wide range of applications, LBN has been gaining more and more attraction among wireless users and service providers. The mainst.eam centralized solution based on cellular networks may incur high service cost. In this paper, we present an innovative scheme called Phoenix, which does not rely on any infrastructure, to implement for location based notification service. In our design, devices (users) across the target area form a dynamic peer-to-peer network, where a user can be a message source, a message carrier, or a message subscriber. When a user meets the message carrier, the user can get a copy of the message. Phoenix keeps messages of interest being circulated in the target area, hence users are being notified. To achieve desired notification performance, Phoenix adaptively controls when a user should take the carrier role and help disseminating a message in order to keep the message "alive", given the fact that message carriers may leave the target area and drop the message. Extensive simulations have been conducted to show the efficacy of Phoenix notification system. © 2011 IEEE.

关键词： Location based services

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Efficient lp-norm multiple feature metric learning for image categorization 11

Efficient lp-norm multiple feature metric learning for image...

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20th ACM Conference on Information and Knowledge Management, CIKM'11

作者： Wang, Shuhui Huang, Qingming Jiang, Shuqiang Tian, Qi Key Lab. of Intell. Info. Process. Inst. of Comput. Tech. CAS Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100049 China Dept. of Computer Science Univ. of Texas at San Antonio San Antonio TX 78249 United States

ISBN: (纸本)9781450307178

Previous metric learning approaches are only able to learn the metric based on single concatenated multivariate feature representation. However, for many real world problems with multiple feature representation such as image categorization, the model trained by previous approaches will degrade because of sparsity brought by significant dimension growth and uncontrolled influence from each feature channel. In this paper, we propose an efficient distance metric learning model which adapts Distance Metric Learning on multiple feature representations. The aim is to learn the Mahalanobis matrices for each independent feature and their non-sparse lp-norm weight coefficients simultaneously by maximizing the margin of the overall learned distance metric among the pairs from the same class and the distance of pairs from different classes. We further extend this method to nonlinear kernel learning and category specific metric learning, which demonstrate the applicability of using many existing kernels for image data and exploring the hierarchical semantic structures for large scale image datasets. Experiments on various datasets demonstrate the promising power of our method. © 2011 ACM.

关键词： Semantics

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Multi-user private keyword search for cloud computing

Multi-user private keyword search for cloud computing

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2011 3rd IEEE International Conference on Cloud Computing Technology and science, CloudCom 2011

作者： Yang, Yanjiang Lu, Haibing Weng, Jian Institute for Infocomm Research Singapore Singapore Dept. of Operations Management and Information Systems Leavey School of Business Santa Clara University United States Department of Computer Science Emergency Technology Research Center of Risk Evaluation and Prewarning on Public Network Security Jinan University Guangzhou China State Key Laboratory of Information Security Institute of Software Chinese Academy of Sciences China State Key Lab. of Networking and Switching Technology Beijing University of Posts and Telecommunications China

ISBN: (纸本)9780769546223

Enterprises outsourcing their databases to the cloud and authorizing multiple users for access represents a typical use scenario of cloud storage services. In such a case of database outsourcing, data encryption is a good approach enabling the data owner to retain its control over the outsourced data. Searchable encryption is a cryptographic primitive allowing for private keyword based search over the encrypted database. The above setting of enterprise outsourcing database to the cloud requires multi-user searchable encryption, whereas virtually all of the existing schemes consider the single-user setting. To bridge this gap, we are motivated to propose a practical multi-user searchable encryption scheme, which has a number of advantages over the known approaches. The associated model and security requirements are also formulated. We further discuss to extend our scheme in several ways so as to achieve different search capabilities. © 2011 IEEE.

关键词： Outsourcing

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ObjectBook construction for large-scale semantic-aware image retrieval

ObjectBook construction for large-scale semantic-aware image...

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3rd IEEE International Workshop on Multimedia Signal Processing, MMSP 2011

作者： Zhang, Shiliang Tian, Qi Huang, Qingming Gao, Wen Key Lab. of Intelli. Info. Process. Inst. of Comput. Tech. CAS Beijing 100190 China Department of Computer Science University of Texas San Antonio TX78249 United States Graduate University Chinese Academy of Sciences Beijing 100049 China Peking University No. 5 Yiheyuan Road Beijing 100871 China

ISBN: (纸本)9781457714337

Automatic image annotation assigns semantic lab.ls to images thus presents great potential to achieve semantic-aware image retrieval. However, existing annotation algorithms are not scalab.e to this emerging need, both in terms of computational efficiency and the number of tags they can deal with. Facilitated by recent development of the large-scale image category recognition data such as ImageNet, we extrapolate from it a model for scalab.e image annotation and semantic-aware image retrieval, namely ObjectBook. The element in the ObjectBook, which is called an ObjectWord, is defined as a collection of discriminative image patches annotated with the corresponding objects. We take ObjectBook as a high-level semantic preserving visual vocabulary, and hence are able to easily develop efficient image annotation and inverted file indexing strategies for large-scale image collections. The proposed retrieval strategy is compared with state-of-the-art algorithms. Experimental results manifest that the ObjectBook is both discriminative and scalab.e for large-scale semantic-aware image retrieval. © 2011 IEEE.

关键词： Image retrieval

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FECG extraction using wavelet denoising and neural networks approach

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ICIC Express Letters 2011年第3期5卷 667-673页

作者： Yin, Ying Ye, Mao Zhu, Yuanxiang Ren, Dongxiao School of Applied Mathematics School of Computer Science and Engineering University of Electronic Science and Technology of China No. 4 Sec. 2 Jianshe North Road Chengdu 610054 China State Key Lab. for Novel Software Technology Nanjing University 22 Hankou Road Nanjing 210093 China

Neural networks have received much attention in the extraction of fetal electrocardiogram signal in recent years. This paper provides a new method to extract the fetal electrocardiogram signal which uses wavelet denoising and backpropagation algorithm. We suppose there are two signals obtained from thoracic region and abdominal region of a pregnant woman. By denoising the abdominal signal using wavelet, and then subtracting the distorted thoracic signal from the denoised abdominal signal, the fetal electrocardiogram signal is achieved. The distorted thoracic signal is received by backpropagation algorithm because neural networks can uniformly approximate every continuous function if there is sufficient number of neurons in the hidden layer. © 2011 ISSN 1881-803X.

关键词： Extraction

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Particle swarm optimisation with simple and efficient neighbourhood search strategies

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International Journal of Innovative Computing and Applications 2011年第2期3卷 97-104页

作者： Wang, Hui Wu, Zhijian Rahnamayan, Shahryar Li, Changhe Zeng, Sanyou Jiang, Dazhi State Key Lab. of Software Engineering Wuhan University Wuhan 430072 China 2000 Simcoe Street North Oshawa ON L1H 7K4 Canada Department of Computer Science University of Leicester Leicester LE1 7RH United Kingdom School of Computer Sciences China University of Geosciences Wuhan 430074 China Department of Computer Science Shantou University Shantou 515063 China

This paper presents a novel particle swarm optimiser (PSO) called PSO with simple and efficient neighbourhood search strategies (NSPSO), which employs one local and two global neighbourhood search strategies. By this way, one strong and two weak locality perturbation operators are embedded in the standard PSO. The NSPSO consists of two main steps. First, for each particle, three trail particles are generated by the mentioned three neighbourhood search strategies, respectively. Then, the best one among the three trail particles is selected to compete with the current particle, and the fitter one is accepted as a current particle. In order to verify the performance of NSPSO, it experimentally has been tested on 12 unimodal and multimodal benchmark functions. The results show that NPSO significantly outperforms other seven PSO variants. Copyright © 2011 Inderscience Enterprises Ltd.

关键词： Global optimization

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Rationale management challenges in requirements engineering

Rationale management challenges in requirements engineering

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作者： Liang, Peng Avgeriou, Paris He, Keqing State Key Lab. of Software Engineering Computer School Wuhan University China Department of Computing Science University of Groningen Netherlands

ISBN: (纸本)9781424487837

Rationale and rationale management have been playing an increasingly prominent role in software system development mainly due to the knowledge demand during system evaluation, maintenance, and evolution, especially for large and complex systems. The rationale management for requirements engineering, as a commencing and critical phase in software development life cycle, is still under-exploited. In this paper, we first survey briefly the state-of-the-art on rationale employment and applications in requirements engineering. Secondly, we identify the challenges in integrating rationale management in requirements engineering activities in order to promote further investigations and define a research agenda on rationale management in requirements engineering. ©2010 IEEE.

关键词： Knowledge management

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Heterogeneous multi-core parallel SGEMM performance testing and analysis on Cell/B.E processor

Heterogeneous multi-core parallel SGEMM performance testing ...

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IEEE International Conference on Networking, Architecture and Storage

作者： Li, Yan Zhang, Yunquan Wang, Ke Guan, Wenhua Lab. of Parallel Software and Computational Science ISCAS Beijing China State Key Lab. of Computer Science CAS Beijing China Graduate University Chinese Academy of Sciences Beijing China

ISBN: (纸本)9780769541341

Matrix multiplication is one of the most common and vital numerical operations in the field of scientific computing, which is the kernel routine of Level 3 BLAS. The STI CELL processor is a heterogeneous multiprocessor with a unique design to achieve peak floating point performance. As matrix multiplication operation is essential for a wide range of numerical algorithms and single improvement to the GEMM routine immediately can benefits the entire algorithm. In this paper, we provide a new way to utilize the hardware features of Cell to achieve better performance on the single precision general matrix multiplication (SGEMM), by using both of heterogeneous PPEs and SPEs parallelization, our method gain speedup over the Cell SDK. © 2010 IEEE.

关键词： Cells

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