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MultiMedia, IEEE

Issue 1 • Date Jan. 2011

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Displaying Results 1 - 20 of 20
  • [Front cover]

    Publication Year: 2011 , Page(s): c1
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  • [Front cover]

    Publication Year: 2011 , Page(s): c2
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  • Contents

    Publication Year: 2011 , Page(s): 1
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  • Express Yourself

    Publication Year: 2011 , Page(s): 2
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  • Academia Meets Industry at the Multimedia Grand Challenge

    Publication Year: 2011 , Page(s): 4 - 7
    Cited by:  Papers (1)
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  • Social Media on the Road: Mobile Technologies and Future Traffic Research

    Publication Year: 2011 , Page(s): 8 - 10
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (177 KB) |  | HTML iconHTML  

    Many of us spend a lot of time on the road. This article gives insight into the potential for social media to make this time more interesting and meaningful for drivers and passengers. The author illustrates the new field of social media on the road for selected applications that promise to improve driving time by facilitating interaction with the other road users and the surrounding environment. View full abstract»

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  • Large-Scale Multimedia Retrieval and Mining [Guest editors' introduction]

    Publication Year: 2011 , Page(s): 11 - 13
    Cited by:  Papers (1)
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  • Mining Music from Large-Scale, Peer-to-Peer Networks

    Publication Year: 2011 , Page(s): 14 - 23
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (589 KB) |  | HTML iconHTML  

    Millions of users worldwide use peer-to-peer (P2P) networks for sharing content, with a significantly high percentage of this content being multimedia, such as songs and movies.1 As such, P2P networks are an invaluable resource for various multimedia information retrieval (MIR) tasks because of the large data set, the ability to capture data without the collaboration of P2P network oper ators, and a large and diverse population. View full abstract»

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  • Enhancing Bag-of-Words Models with Semantics-Preserving Metric Learning

    Publication Year: 2011 , Page(s): 24 - 37
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (405 KB) |  | HTML iconHTML  

    The authors present an online semantics preserving, metric learning technique for improving the bag-of-words model and addressing the semantic-gap issue. This article investigates the challenge of reducing the semantic gap for building BoW models for image representation; propose a novel OSPML algorithm for enhancing BoW by minimizing the semantic loss, which is efficient and scalable for enhancing BoW models for large-scale applications; apply the proposed technique for large-scale image annotation and object recognition; and compare it to the state of the art. View full abstract»

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  • Mining Event Structures from Web Videos

    Publication Year: 2011 , Page(s): 38 - 51
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1208 KB) |  | HTML iconHTML  

    The article is discussing the issues of mining event structures from Web video search results using text analysis, burst detection, and clustering as with the proliferation of social media, the volume of Web videos have grown exponentially. View full abstract»

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  • Cluster-Based Landmark and Event Detection for Tagged Photo Collections

    Publication Year: 2011 , Page(s): 52 - 63
    Cited by:  Papers (11)
    Multimedia
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (897 KB) |  | HTML iconHTML  

    An image analysis scheme can automate the detection of landmarks and events in large image collections, significantly improving the content-consumption experience. View full abstract»

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  • RanKloud: Scalable Multimedia Data Processing in Server Clusters

    Publication Year: 2011 , Page(s): 64 - 77
    Cited by:  Papers (1)
    Multimedia
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (501 KB) |  | HTML iconHTML  

    Multimedia data is produced in massive quantities. The applications that drive this massive data influx today span a large spectrum, from entertainment, surveillance, and e-commerce to Web content and social media. This data flood brings forth a need for highly parallelizable frameworks for scalable processing and efficient analysis of large media collections.In this article, we have observed that a major obstacle in executing large media-analysis operations in a scalable manner is that, when implemented naively, a significant portion of the work might be wasted. RanKloud is a system we are developing for share-nothing, batched parallelization of large media-analysis operations in a waste-avoiding manner. RanKloud achieves this by treating the utility of the data and features to the given analysis as an integral part of the process and by developing data partitioning and resource strategies that consider the ranked semantics of the analysis operations as well as data and utility characteristics discovered at runtime. Future work will include extension of the RanKloud framework with new primitives and investigation of the application of RanKloud to various large-scale multimedia data analysis applications. View full abstract»

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  • Online Video Recommendation through Tag-Cloud Aggregation

    Publication Year: 2011 , Page(s): 78 - 87
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (340 KB)  

    A framework for recommending online videos operates by constructing user profiles as an aggregate of tag clouds and generating recommendations according to similar viewing patterns. View full abstract»

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  • Upcoming Events

    Publication Year: 2011 , Page(s): 87
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  • Visual Rhythm Detection and Its Applications in Interactive Multimedia

    Publication Year: 2011 , Page(s): 88 - 95
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (465 KB) |  | HTML iconHTML  

    True multimedia experience involves multimodal media and their intrinsic interactions. This article identifies rhythm as the link between physical movement, other visual stimuli, and the musical art form. It describes two example interactive multimedia applications in which visual rhythm is extracted for synchronization of music and video to allow more intuitive interaction between a user and both audio and video content, leaving the door open for many potential innovative applications. View full abstract»

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  • Thanks to IEEE MultiMedia's Reviewers

    Publication Year: 2011 , Page(s): 96 - 97
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  • Multimodal Input in the Car, Today and Tomorrow

    Publication Year: 2011 , Page(s): 98 - 103
    Cited by:  Papers (5)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (268 KB) |  | HTML iconHTML  

    With the increased functionality offered by in-vehicle systems, multimodal input is emerging as an effective means of interaction to minimize driver distraction. This article describes the current state of this technology for automotive applications, various ways to combine modalities, and outlooks toward the future. View full abstract»

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  • New Products

    Publication Year: 2011 , Page(s): 104
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  • [Advertisement - Back cover]

    Publication Year: 2011 , Page(s): c3
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  • [Advertisement - Back cover]

    Publication Year: 2011 , Page(s): c4
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Aims & Scope

The magazine contains technical information covering a broad range of issues in multimedia systems and applications

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
John R. Smith
IBM T.J. Watson Research Center