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检索条件"机构=Signal Processing and Multimedia Group Department of Electrical and Computer Engineering"

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The participation payoff: Challenges and opportunities for multimedia access in networked communities

The participation payoff: Challenges and opportunities for m...

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2010 ACM SIGMM International Conference on multimedia Information Retrieval, MIR 2010

作者： Ramzan, Naeem Larson, Martha Dufaux, Frédéric Clüver, Kai Multimedia and Vision Group School of Electronic Eng. and Computer Science Queen Mary University of London United Kingdom Multimedia Information Retrieval Lab Elec. Eng. Mathematics and Computer Science Delft University of Technology Netherlands Multimedia Signal Processing Group Institute of Electrical Engineering Ecole Polytechnique Fédérale de Lausanne Switzerland Communication Systems Group Technische Universität Berlin Germany

ISBN: (纸本)9781605588155

Increasingly, multimedia collections are associated with networked communities consisting of interconnected groups of users who create, annotate, browse, search, share, view, critique and remix collection content. Information arises within networked communities via connections among users and in the course of interactions between users and content. Community-derived information can be exploited to improve user access to multimedia. This paper provides a survey of techniques that make use of a combination of three information sources: community-contributed information (e.g., tags and ratings), network structure and techniques for multimedia content analysis. This triple synergy offers a wide range of opportunities for improving access to multimedia in networked communities. We focus our survey on three areas important for multimedia access: annotation, distribution and retrieval. The picture that emerges is promising: information derived from the social community is remarkably effective in improving access to multimedia content, and participation in networked communities has a high payoff. Copyright 2010 ACM.

关键词： Surveys

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Perceptual tagging of video files in P2P networks

Perceptual tagging of video files in P2P networks

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IEEE International Conference on Image processing

作者： Alper Koz R. L. Lagendijk Multimedia Signal Processing Group Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technnology Netherlands

Identification of a video file in current peer-to-peer (P2P) networks is achieved by its tag or by a (100-200 bits) cryptographic hash of the entire file. However, these approaches fail when the tag is changed or some small insertions, deletions or format changes are applied to the video by a user in the network. A complementary approach is to tag a video with a few hundreds of bits of information, which we call perceptual tags, extracted from perceptual features of the content robust to typical processing. In this paper, we first give the basic requirements for the extraction and distribution of these perceptual tags in a P2P network considering the characteristics of the peers (ordinary internet users), such as low computational power and low bandwidth. Then, we propose a novel method that extracts N (64-256) bits of robust perceptual tags for a video file by using only the mean of video frames. The proposed method also achieves the uniform distribution of perceptual tags among the peers needed for the state of the art DHT-based indexing implementations in P2P networks.

关键词： Peer to peer computing Synchronization Histograms Robustness Feature extraction Indexing Tagging

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PERCEPTUAL VIDEO HASHING IN P2P NETWORKS

PERCEPTUAL VIDEO HASHING IN P2P NETWORKS

引用

IEEE International Conference on Acoustics, Speech, and signal processing

作者： Alper Koz R.(Inald) L. Lagendijk Multimedia Signal Processing Group Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology The Netherlands

ISBN: (纸本)9781424442959

Content identification in peer-to-peer (P2P) networks has until now been achieved by using metadata or cryptographic hashes. However, with increasing number of duplicates in different names and formats especially in (unmanaged) P2P networks, these tools have become insufficient for proper content finding and access right management. A complementary possible approach is to identify the content in P2P networks by using perceptual hashes, (or fingerprints) extracted from the perceptual features of the content robust to typical processing. In this paper, we first discuss the essential differences in fingerprint size, fingerprint extraction complexity, and fingerprint search methodology for a video identification system in P2P networks compared with central database applications. Then we propose a novel method optimized for P2P networks that uses only differences of video frame means. The proposed method reduces the fingerprint sizes into kilobytes, extraction time to seconds, and search duration into milliseconds. Furthermore, the uniform distribution of the extracted fingerprints enables the usage of existing DHT-based keyword search methods for fingerprint queries.

关键词： Peer to Peer Perceptual Hash Fingerprint Content Search Access Right Management Video Identification Fingerprints P2P network peer to peer Videotapes

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New rate distortion bounds for speech coding based on composite source models

New rate distortion bounds for speech coding based on compos...

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Information Theory and Applications Workshop, ITA

作者： Jerry D. Gibson Jing Hu Pravin Ramadas Department of Electrical and Computer Engineering University of California Santa Barbara USA Digital Signal processing Group Cisco Systems Inc. USA

We present new rate distortion bounds for speech coding based upon new composite source models for speech and conditional rate distortion theory. The composite source models are constructed by classifying each sentence as Voiced (V), Unvoiced (UV), Onset (ON), Hangover (H), and Silence (S). A 10 th order AR model is used for the V mode, 4 th order AR models are used for the ON and H modes, and the UV mode is modeled as uncorrelated. Marginal rate distortion functions are computed for each mode and combined to produce conditional rate distortion bounds based on unweighted and weighted mean squared error distortion measures. For unweighted distortion measures, the new bounds imply that good performance is attainable at rates as low as 0.25 bits/sample for narrowband speech.

关键词： Rate-distortion Speech coding Distortion measurement Rate distortion theory Speech codecs Predictive models Digital signal processing Speech processing Narrowband Mathematical model

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Rate distortion bounds for blocking and intra-frame prediction in videos

Rate distortion bounds for blocking and intra-frame predicti...

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IEEE Information Theory and Applications Workshop

作者： Hu, Jing Gibson, Jerry D. Digital Signal Processing Group Cisco Systems Department of Electrical and Computer Engineering University of California Santa Barbara United States

ISBN: (纸本)9781424439904

Recently we proposed a block-based conditional correlation coefficient model for natural videos in the spatial-temporal domain. The conditioning is on local texture and the optimal parameters can be calculated for a specific video with a mean absolute error (MAE) usually smaller than 5%. We used this conditional correlation model and the classic results on conditional rate distortion functions to calculate new theoretical rate distortion bounds for videos which appear to be the only valid theoretical rate distortion bounds with regard to the current cutting-edge video compression technologies such as those standardized in AVC/H.264. In this paper, we focus on utilizing the new block-based local-texture-dependent correlation model to derive rate distortion bounds for blocking and optimal prediction across neighboring blocks. We study the penalty paid in average rate when the correlation among the neighboring blocks is discarded completely or is incorporated partially through predictive coding. We calculate the thresholds in average rate and distortion when incorporating the correlation among the neighboring blocks through optimal predictive coding becomes worse than completely discarding this correlation. We also discuss the role of local texture in inter-frame prediction.

关键词： Forecasting

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Bayesian decision for the fusion center of abstract distributed network in Cognitive Radio

Bayesian decision for the fusion center of abstract distribu...

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2009 IEEE International Conference on signal and Image processing Applications, ICSIPA09

作者： Mosleh, S. Tadaion, A.A. Derakhtian, M. Signal Processing Research Group Department of Electrical and Computer Engineering Yazd University Yazd Iran Department of Electrical Engineering Shiraz University Shiraz Iran

ISBN: (纸本)9781424455614

Cognitive Radio (CR) allows for usage of licensed frequency band by unlicensed Secondary Users (SU)s. However, these SUs need to monitor the spectrum continuously to avoid possible interference with the licensed Primary users (PU)s. In order to avoid causing harmful interference to a PU that is in operation, spectrum sensing is needed for the CRs. One of the great challenges of spectrum sensing is to detect the presence of the PU with little information about the channel and the signal transmitted from the PU. Cooperative spectrum sensing has been shown to greatly increase the probability of detecting the PU. Cooperative spectrum sensing refers to the spectrum sensing methods where local spectrum sensing information from multiple SUs are combined for PU detection. Distributed spectrum sensing methods have the potential to increase the spectral estimation reliability and decrease the probability of interference of CRs to primary communications. This paper considers the performance of a distributed Bayesian detection system consisting of N sensors and a fusion center, in which the decision rules of the sensors have been given and the decisions of different sensors are mutually independent conditioned on both hypotheses. Theoretical analysis on the performance of this fusion center is carried out. We obtain the conditions for the fusion center such that achieves the minimum average cost of making a decision for the overall system is smaller than the local risk of each sensor. The performance of our detector is compared to the traditional AND, OR and Majority decision fusion rules and numerical results show that AND, OR and Majority decision fusion rules are the special cases of the Bayesian fusion rule. In addition, we derive a lower bound for the risk of the fusion center for any given priori probability of hypothesis.

关键词： Data fusion

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Rate distortion bounds for blocking and intra-frame prediction in videos

Rate distortion bounds for blocking and intra-frame predicti...

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43rd Asilomar Conference on signals, Systems and computers

作者： Hu, Jing Gibson, Jerry D. Cisco Systems Digital Signal Processing Group United States Department of Electrical and Computer Engineering University of California Santa Barbara United States

ISBN: (纸本)9781424458271

Recently we revisited the classic problem of developing a correlation model for natural videos by proposing a blockbased local-texture-dependent correlation coefficient model for natural videos in the original spatial-temporal domain prior to any processing. We used this conditional correlation model to calculate the conditional rate distortion function when universal side information on local texture is available at both the encoder and the decoder. We demonstrated that this conditional rate distortion bound is indeed a valid lower bound with respect to the operational rate distortion curves of both intra-frame and inter-frame coding in AVC/H.264. Besides the theoretical lower bounds, we also produced a practical lower bound for a single video frame based on the new conditional correlation model and a few assumptions on intra-frame video coding. In this paper we extend the work of generating practical rate distortion bounds for natural videos from a single frame to multiple frames and examine the relationship between texture and motion, the two most dominant visual aspects in natural videos. © 2009 IEEE.

关键词： Image coding

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On the Convergence of Perturbed Non-Stationary Consensus Algorithms

On the Convergence of Perturbed Non-Stationary Consensus Alg...

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

作者： T. C. Aysal K. E. Barner Communications Research in Signal Processing Group School of Electrical and Computer Engineering Cornell University Ithaca NY USA Signal Processing and Communications Group Electrical and Computer Engineering Department University of Delaware Newark DE USA

ISBN: (纸本)9781424435128

We consider consensus algorithms in their most general setting and provide conditions under which such algorithms are guaranteed to converge, almost surely, to a consensus. Let {A(t),B(t)} isin R N times N be (possibly) random, non-stationary matrices and {x(t),m(t)} isin R N times 1 be state and perturbation vectors, respectively. For any consensus algorithm of the form x(t + 1) = A(t)x(t) + B(t)m(t), we provide conditions under which consensus is achieved almost surely, i.e., Pr {lim trarrinfin x(t) = c1} = 1 for some c isin R. Moreover, we show that this general result subsumes recently reported results for specific consensus algorithms classes, including sum-preserving, non-sum-preserving, quantized and noisy gossip algorithms. Also provided are the e-converging time for any such converging iterative algorithm, i.e., the earliest time at which the vector x(t) is e close to consensus, and sufficient conditions for convergence in expectation to the initial node measurements average.

关键词： Convergence signal processing algorithms Iterative algorithms Peer to peer computing Computational modeling Communications Society Sufficient conditions Time measurement Ad hoc networks Application software

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Iteratively detected MIMO-OFDM twisted-pair transmission schemes

Iteratively detected MIMO-OFDM twisted-pair transmission sch...

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作者： Ahrens, Andreas Lange, Christoph Department of Electrical Engineering Computer Science Communications Signal Processing Group University of Technology Philipp-Müller-Straße 14 23966 Wismar Germany T-Systems Enterprise Services GmbH Goslarer Ufer 35 Berlin 10589 Germany

ISBN: (纸本)9783642051968

Crosstalk between neighbouring wire pairs in multi-pair copper cables is an important disturbance, which essentially limits the transmission quality and the throughput of such cables. For high-rate transmission, often the strong near-end crosstalk (NEXT) disturbance is avoided or suppressed and only the far-end crosstalk (FEXT) remains as crosstalk influence. In this contribution the FEXT impact in iteratively detected MIMO-OFDM transmission schemes is studied. Extrinsic information transfer (EXIT) charts are used for analyzing and optimizing the convergence behaviour of the iterative demapping and decoding. Our results show that FEXT is not necessarily a limiting factor if appropriate signal processing strategies are used. © 2009 Springer-Verlag Berlin Heidelberg.

关键词： Orthogonal frequency division multiplexing

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Bayesian decision for the fusion center of a distributed network in Cognitive Radio

Bayesian decision for the fusion center of a distributed net...

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IEEE International Conference on signal and Image processing Applications (ICSIPA)

作者： S. Mosleh A.A. Tadaion M. Derakhtian Signal Processing Research Group Department of Electrical and Computer Engineering Yazd University Yazd Iran Department of Electrical Engineering Shiraz University Shiraz Iran

关键词： Bayesian methods Cognitive radio Sensor fusion Sensor systems Interference Chromium Frequency Monitoring Performance analysis Costs

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