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IEEE Annual Conference on Decision and Control

作者： Junlin Xiong Alexander Lanzon Ian R. Petersen CAS Key Lab of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei 230026 China Control Systems Centre School of Electrical and Electronic Engineering University of Manchester Manchester M13 9PL U.K. School of Engineering and Information Technology University of New South Wales at the Australian Defence Force Academy Canberra ACT 2600 Australia

ISBN: (纸本)9781479978878

This paper is concerned with negative imaginary lemmas for descriptor systems. Without the minimal state-space realization assumption, sufficient conditions are developed for a negative imaginary lemma and a strictly negative imaginary lemma, respectively. As corollaries, sufficient conditions are derived to ensure the systems are both admissible and negative imaginary. Also, new sufficient negative imaginary lemmas are found for standard linear systems as special cases. The developed negative imaginary lemmas are applicable to descriptor systems with impulse modes. Two examples are used to illustrate the theory.

关键词： Theorem Negative Linear system Descriptors Lemma Sufficient conditions

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A Multicast Architecture of SVC Streaming Over OpenFlow Networks

A Multicast Architecture of SVC Streaming Over OpenFlow Netw...

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IEEE Global Communications Conference

作者： Enzhong Yang Yongyi Ran Shuangwu Chen Jian Yang CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China

ISBN: (纸本)9781479935130

In video streaming service, multicast mode is a promising way to complement unicast delivery of content, since it deliveries the video content to a broad range of receivers. It is considered as an efficient scheme to reduce redundant traffic in the networks. In this paper, we propose an OpenFlow based architecture for implementing Scalable Video Coding (SVC) multicast streaming. It enables in-network identifying, processing and manipulating the media streams, which makes prompt bitrate adaptation possible in response to network fluctuations. The heterogeneous video quality demand from the heterogeneous device also can be satisfied by customizing the multicast traffic through a centralized OpenFlow controller. We implement a testbed following the proposed architecture in our campus. With OpenFlow, we deploy IP multicast in a new way without Internet Group Management Protocol (IGMP) or any multicast addresses. Experiments implemented on the testbed show that our approach can provide a flexible and controllable video multicast streaming service and improve the usage of bandwidth resource in the condition of guaranteeing multicast receivers' Quality of Experience (QoE).

关键词： IP networks multicast communication telecommunication traffic video coding video streaming IP multicast OpenFlow networks bandwidth resource usage improvement bitrate adaptation centralized OpenFlow controller controllable video multicast streaming service heterogeneous device heterogeneous video quality demand media streams multicast SVC streaming architecture multicast receivers quality-of-experience multicast traffic network fluctuations redundant traffic reduction scalable video coding multicast streaming unicast content delivery Control systems Ports (Computers) Receivers Servers Static VAr compensators Streaming media

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Category-based dynamic recommendations adaptive to user interest drifts

Category-based dynamic recommendations adaptive to user inte...

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International Conference on Wireless Communications and Signal processing (WCSP)

作者： Kaixiang Lin Dong Liu CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China

ISBN: (纸本)9781479973408

How to make dynamic recommendations under volatile user interest drifts has been a problem of great interest in modern recommender systems, where challenges lie in accurate and efficient measurement, modeling, and prediction of the user interest drifts. This paper studies a category-based approach to the problem with the key idea that items are aggregated into categories and recommendations are made on each category. In our approach, we use the category-wise rating matrix to measure the changing preferences of users; we design a dynamic adaptive model (DAM) to describe the patterns of interest drifts; and we utilize linear regression to predict the future interests of users in a category-based manner. We have built a category-based dynamic recommender system and tested it with two well-known datasets. Experimental results show that our proposed approach achieves superior performance on category-based rating prediction compared with state-of-the-art dynamic recommendation algorithms.

关键词： Vectors Adaptation models Clustering algorithms Recommender systems Optimization Predictive models Data models

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Visualization of user interests in online music services

Visualization of user interests in online music services

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IEEE International Conference on Multimedia and Expo Workshops (ICMEW)

作者： Jingxian Zhang Dong Liu CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China

ISBN: (纸本)9781479947164

Online music services have been popular for end users to obtain music, where user interests, as reflected by their downloading records, are crucial for service providers to understand users and thus to provide personalization. However, the raw downloading records are of huge volume and difficult to analyze intuitively. We study a visualization approach to analyzing downloading records so as to present user interests. To reveal the underlying relevance between music tracks, we utilized not only the metadata of music (especially genres), but also collaborative relevance that is voted by users. To present time varying user interests, we designed several new figures, namely Bean plot, Instrument plot, and Transitional Pie plot, that are capable in displaying different aspects of user interests variation. We have performed experiments with a real-world data set, and the results show the effectiveness of our proposed visualization method. Our work is also inspiring for visualization of time varying data in other applications.

关键词： Instruments Collaboration Color Statistical distributions Data visualization Neck Educational institutions

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Image annotation via social diffusion analysis with common interests

Image annotation via social diffusion analysis with common i...

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IEEE International Conference on Multimedia and Expo Workshops (ICMEW)

作者： Chenyi Lei Dong Liu CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China

Automatic annotation of images is of crucial importance in image retrieval and management systems. Most of the existing annotation methods rely on content-based approach to annotation, whose effectiveness is restricted due to the semantic gap between low-level features and semantic annotations, as well as the irrelevance between annotations and image content. Recently, social media analysis has been investigated for image annotation. Inspired by the abundant social diffusion records of images in online social networks, we propose a novel image annotation approach based on social diffusion analysis. We present a common-interest model to interpret social diffusion, i.e. different images have different social diffusion routes due to the preferences of users, and such preferences are represented as common interests of pairwise users rather than personalized interests. We propose an image annotation framework that consists of learning of common interests, feature extraction from social diffusion records, and automatic annotation by learning to rank. Experimental results on a real-world dataset show that our proposed approach outperforms content-based and user-preference-based annotation methods.

关键词： Abstracts Vectors Positron emission tomography

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Hybrid transform for HEVC-based lossless coding

Hybrid transform for HEVC-based lossless coding

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IEEE International Symposium on Circuits and systems (ISCAS)

作者： Fangdong Chen Jinlei Zhang Houqiang Li CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China

ISBN: (纸本)9781479934331

The High Efficiency Video Coding (HEVC) with the transform bypass mode is simple but inefficient for lossless coding. For this reason, we propose a novel transform to further eliminate the redundancy between residues of different blocks in intra prediction. Dependent on intra prediction modes, the proposed transform is adaptable to exploit correlations of residues formed by different modes. In order to accurately obtain parameters of the transform matrix, an approach similar to the Wiener filtering method is adopted. Experimental results show that on top of the lossless coding mode in HEVC, our method offers the performance with a 7.4% bit-rate reduction on average for All Intra Main configuration. Compared with other representative algorithms, our proposal still shows an improvement in the compression ratio, without substantial increases of computational complexity in the encoder or decoder.

关键词： Encoding Transforms Video coding Redundancy Prediction algorithms Proposals Standards

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QUERY DIFFICULTY ESTIMATION VIA PSEUDO RELEVANCE FEEDBACK FOR IMAGE SEARCH

QUERY DIFFICULTY ESTIMATION VIA PSEUDO RELEVANCE FEEDBACK FO...

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IEEE International Conference on Multimedia and Expo

作者： Qianghuai Jia Xinmei Tian Tao Mei CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Microsoft Research

ISBN: (纸本)9781479947607

Query difficulty estimation (QDE) attempts to automatically predict the performance of the search results returned for a given query. QDE has been widely investigated in text document retrieval for many years. However, few research works have been explored in image retrieval. State-of-the-art QDE methods in image retrieval mainly investigate the statistical characteristics (coherence, robustness, etc.) of the returned images to derive a value for indicating the query difficulty degree. To the best of our knowledge, little research has been done to directly estimate the real retrieval performance of the search results, such as average precision, instead of only an indicator. In this paper, we propose a novel query difficulty estimation approach which automatically estimate the average precision of the image search results. Specifically, we first select a set of query relevant and query irrelevant images for each query via pseudo relevance feedback. Then an efficient and effective voting scheme is proposed to estimate the relevance label of each image in the search results. Based on the images' relevance labels, the average precision of the search results returned for the given query is derived. The experimental results on a benchmark image search dataset demonstrate the effectiveness of the proposed method.

关键词： Query difficulty estimation (QDE) Image retrieval Average precision (AP) Pseudo relevance feedback (PRF) Voting scheme

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SIFT-preserving compression of mobile-captured license plate images for recognition

SIFT-preserving compression of mobile-captured license plate...

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International Conference on Wireless Communications and Signal processing (WCSP)

作者： Dandan Wang Dong Liu CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China

ISBN: (纸本)9781479973408

Image compression had been extensively studied for reducing coding rate yet producing acceptable visual quality. However, there are many application scenarios where the compressed images are used for automatic recognition rather than human viewing, thus the visual quality is no longer critical for compression. SIFT features have demonstrated their utility in many recognition scenarios and SIFT-preserving compression is developed recently. In this paper, we firstly study the SIFT-preserving compression of license plate images for recognition accuracy rather than visual quality. According to extracted SIFT features, each image is divided into SIFT coding-units and non-SIFT coding-units. Each coding-unit is assigned with a different quality parameter when using JPEG for compression. We compare our proposed scheme with the standard JPEG that uses a unified quality parameter. Experimental results with manually tuned parameters show that on average 14% bit-rate can be saved by our scheme, without any loss of recognition accuracy.

关键词： Image coding Transform coding Licenses Standards Image recognition Feature extraction Accuracy

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A New Non-local Video Denoising Scheme Using Low-Rank Representation and Total Variation Regularization

A New Non-local Video Denoising Scheme Using Low-Rank Repres...

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IEEE International Symposium on Circuits and systems

作者： Qingbo Lu Zhenbo Lu Xiaoqing Tao Houqiang Li CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei Anhui China

ISBN: (纸本)9781479934331

In this article, we present a novel non-local video denoising scheme using low-rank representation and total variation regularization. The proposed scheme attempts to make full use of the intrinsic properties that the grouping similar patches not only lie in a low-rank subspace but are also sparse in total variation (TV) domain. For a group of similar patches, we formulate video denoising problem into a concise model that combines nuclear norm, TV regularization and l_1 norm. The experiments demonstrate that the proposed scheme is capable of handling multi-type noise including dense Gaussian noise and random-valued sparse noise, while maintaining the texture information meantime. The results show that our scheme achieves noticeable performance improvement over the state-of-the-art video denoising methods.

关键词： video denoising low-rank representation total variation alternating direction method

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A new method for image understanding and retrieval using text-mined knowledge

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8933卷 684-694页

作者： Tian, Jing Huang, Tinglei Huang, Y. Zhang, Z. Guo, Zhi Fu, Kun Key Laboratory of Technology in Geo-spatial Information Processing and Application Systems Institute of Electronics Chinese Academy of Sciences No.19 North 4th Ring Road West Haidian District Beijing100190 China University of Chinese Academy of Sciences No.19A Yuquan Road Shijingshan District Beijing100049 China

Existing approaches for image annotation generally demand training data with exact image labels or human-generated tags, which are often difficult to obtain. In this paper we present a novel model that utilizes the rich surrounding text of images to perform image annotation. Our work makes two main contributions. First, by integrating the state-of-the-art text analysis methods, words that describe the salient objects in images are extracted. Second, a new probabilistic topic model is built to jointly model image features, extracted words and surrounding text. Our model is demonstrated to be flexible enough to handle multi-modal features and provide better annotation prediction performance than the baseline model proposed in previous research. © Springer International Publishing Switzerland 2014.

关键词： Image annotation

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