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Signal Processing Magazine, IEEE

Issue 2 • Date March 2006

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Displaying Results 1 - 25 of 38
  • IEEE Signal Processing Magazine - March 2006 - Vol. 23 No. 2

    Publication Year: 2006 , Page(s): 0_1
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  • Table of contents

    Publication Year: 2006 , Page(s): 1
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  • "First who ... Then what" [from the Editor]

    Publication Year: 2006 , Page(s): 2
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  • Fiscal strength [President's message]

    Publication Year: 2006 , Page(s): 4
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  • Members-at-Large - Call for nominations

    Publication Year: 2006 , Page(s): 5
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  • SPS Members receive IEEE-USA Awards

    Publication Year: 2006 , Page(s): 5
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  • Looking back and to the future - leadership from a Swedish perspective

    Publication Year: 2006 , Page(s): 6 - 8
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  • Signal processing outreach at the U.S. Naval Academy

    Publication Year: 2006 , Page(s): 10 - 16
    Cited by:  Papers (1)
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  • ISSPIT 2006 - Call for Papers

    Publication Year: 2006 , Page(s): 13
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  • Semantic retrieval of multimedia [from the Guest Editors]

    Publication Year: 2006 , Page(s): 14 - 16
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  • 2006 DSP & SPE Workshop - Call for Papers

    Publication Year: 2006 , Page(s): 17
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  • Semantic retrieval of video - review of research on video retrieval in meetings, movies and broadcast news, and sports

    Publication Year: 2006 , Page(s): 18 - 27
    Cited by:  Papers (20)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1309 KB) |  | HTML iconHTML  

    This paper reviews the different research works on three types of video, i.e., video of meetings, movies and broadcast news, and sports video. The paper puts them into a general framework of video summarization, browsing, and retrieval. It also reviews different video representation techniques for these three types of video content within this general framework. Finally, the challenges facing the video retrieval research community are presented View full abstract»

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  • Video shot detection and condensed representation. a review

    Publication Year: 2006 , Page(s): 28 - 37
    Cited by:  Papers (57)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1020 KB) |  | HTML iconHTML  

    There is an urgent need to develop techniques that organize video data into more compact forms or extract semantically meaningful information. Such operations can serve as a first step for a number of different data access tasks such as browsing, retrieval, genre classification, and event detection. In this paper, we focus not on the high-level video analysis task themselves but on the common basic techniques that have been developed to facilitate them. These basic tasks are shot boundary detection and condensed video representation View full abstract»

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  • Semantic event detection via multimodal data mining

    Publication Year: 2006 , Page(s): 38 - 46
    Cited by:  Papers (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1120 KB) |  | HTML iconHTML  

    This paper presents a novel framework for video event detection. The core of the framework is an advanced temporal analysis and multimodal data mining method that consists of three major components: low-level feature extraction, temporal pattern analysis, and multimodal data mining. One of the unique characteristics of this framework is that it offers strong generality and extensibility with the capability of exploring representative event patterns with little human interference. The framework is presented with its application to the detection of the soccer goal events over a large collection of soccer video data with various production styles View full abstract»

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  • Browsing sports video: trends in sports-related indexing and retrieval work

    Publication Year: 2006 , Page(s): 47 - 58
    Cited by:  Papers (12)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3917 KB) |  | HTML iconHTML  

    This paper aims to identify the current trends in sports-based indexing and retrieval work. It discusses the essential building blocks for any semantic-level retrieval system and acts as a case study in content analysis system design. While one of the major benefits of digital media and digital television in particular has been to provide users with more choices and a more interactive viewing experience, the freedom to choose has in fact manifested as the freedom to choose from the options the broadcaster provides. It is only through the use of automated content-based analysis that sports viewers will be given a chance to manipulate content at a much deeper level than that intended by broadcasters, and hence put true meaning into interactivity View full abstract»

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  • Threading and autodocumenting news videos: a promising solution to rapidly browse news topics

    Publication Year: 2006 , Page(s): 59 - 68
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1712 KB) |  | HTML iconHTML  

    This paper describes the techniques in threading and autodocumenting news stories according to topic themes. Initially, we perform story clustering by exploiting the duality between stories and textual-visual concepts through a co-clustering algorithm. The dependency among stories of a topic is tracked by exploring the textual-visual novelty and redundancy of stories. A novel topic structure that chains the dependencies of stories is then presented to facilitate the fast navigation of the news topic. By pruning the peripheral and redundant news stories in the topic structure, a main thread is extracted for autodocumentary View full abstract»

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  • Automatic multimedia indexing: combining audio, speech, and visual information to index broadcast news

    Publication Year: 2006 , Page(s): 69 - 78
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1291 KB) |  | HTML iconHTML  

    This paper describes an indexing system that automatically creates metadata for multimedia broadcast news content by integrating audio, speech, and visual information. The automatic multimedia content indexing system includes acoustic segmentation (AS), automatic speech recognition (ASR), topic segmentation (TS), and video indexing features. The new spectral-based features and smoothing method in the AS module improved the speech detection performance from the audio stream of the input news content. In the speech recognition module, automatic selection of acoustic models achieved both a low WER, as with parallel recognition using multiple acoustic models, and fast recognition, as with the single acoustic model. The TS method using word concept vectors achieved more accurate results than the conventional method using local word frequency vectors. The information integration module provides the functionality of integrating results from the AS module, TS module, and SC module. The story boundary detection accuracy was improved by combining it with the AS results and the SC results compared to the sole TS results View full abstract»

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  • Techniques for movie content analysis and skimming: tutorial and overview on video abstraction techniques

    Publication Year: 2006 , Page(s): 79 - 89
    Cited by:  Papers (30)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1572 KB) |  | HTML iconHTML  

    With the proliferation of digital video, video summarization and skimming has become an indispensable tool of any practical video content management system. This paper provides a tutorial on the existing abstraction work for generic videos and presents state-of-the-art techniques for feature film skimming. The paper also describes the authors' recent work on movie skimming using audiovisual tempo analysis and specific cinematic rules. With the maturity of the movie genre classification, content understanding and video abstraction techniques, an automatic movie content analysis system that facilitates navigation, browsing, and search of desired movie content is possible in the near future View full abstract»

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  • Extracting moods from pictures and sounds: towards truly personalized TV

    Publication Year: 2006 , Page(s): 90 - 100
    Cited by:  Papers (23)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1119 KB) |  | HTML iconHTML  

    This paper considers how we feel about the content we see or hear. As opposed to the cognitive content information composed of the facts about the genre, temporal content structures and spatiotemporal content elements, we are interested in obtaining the information about the feelings, emotions, and moods evoked by a speech, audio, or video clip. We refer to the latter as the affective content, and to the terms such as happy or exciting as the affective labels of an audiovisual signal. In the first part of the paper, we explore the possibilities for representing and modeling the affective content of an audiovisual signal to effectively bridge the affective gap. Without loosing generality, we refer to this signal simply as video, which we see as an image sequence with an accompanying soundtrack. Then, we show the high potential of the affective video content analysis for enhancing the content recommendation functionalities of the future PVRs and VOD systems. We conclude this paper by outlining some interesting research challenges in the field View full abstract»

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  • Pictures are not taken in a vacuum - an overview of exploiting context for semantic scene content understanding

    Publication Year: 2006 , Page(s): 101 - 114
    Cited by:  Papers (11)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2307 KB) |  | HTML iconHTML  

    Considerable research has been devoted to the problem of multimedia indexing and retrieval in the past decade. However, limited by state-of-the-art in image understanding, the majority of the existing content-based image retrieval (CBIR) systems have taken a relatively low-level approach and fallen short of higher-level interpretation and knowledge. Recent research has begun to focus on bridging the semantic and conceptual gap that exists between man and computer by integrating knowledge-based techniques, human perception, scene content understanding, psychology, and linguistics. In this article, we provide an overview of exploiting context for semantic scene content and understanding View full abstract»

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  • Semantic retrieval of multimedia by concept languages: treating semantic concepts like words

    Publication Year: 2006 , Page(s): 115 - 123
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (884 KB) |  | HTML iconHTML  

    This paper presents a retrieval approach that uses concept languages to deal with nonverbally expressed information in multimedia. In operation, a finite number of elecepts of a concept language are identified and used to index multimedia documents. The elecepts then allow a large number of compound semantic queries to be expressed and operated as sentences of elecepts. We believe that managing semantics by concept languages is a prudent proposition. Not only does it extend an intuitive query regime where semantic queries can be specified more expressively and extensively, the approach also allows concept detection to be restricted to a more manageable sum of semantic classes. Two example applications are discussed in the paper. One uses a color artistry language to retrieve art images and the other utilizes a tennis concept language to retrieve tennis videos View full abstract»

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  • Semantic segmentation and summarization of music: methods based on tonality and recurrent structure

    Publication Year: 2006 , Page(s): 124 - 132
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1184 KB) |  | HTML iconHTML  

    This paper describes a study on automatic music segmentation and summarization from audio signals. The paper inquires scientifically into the nature of human perception of music and offers a practical solution to difficult problems of machine intelligence for automated multimedia content analysis and information retrieval. Specifically, three problems are addressed: segmentation based on tonality analysis, segmentation based on recurrent structural analysis, and summarization. Experimental results are evaluated quantitatively, demonstrating the promise of the proposed methods View full abstract»

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  • Automatic genre classification of music content: a survey

    Publication Year: 2006 , Page(s): 133 - 141
    Cited by:  Papers (47)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (641 KB) |  | HTML iconHTML  

    This paper reviews the state-of-the-art in automatic genre classification of music collections through three main paradigms: expert systems, unsupervised classification, and supervised classification. The paper discusses the importance of music genres with their definitions and hierarchies. It also presents techniques to extract meaningful information from audio data to characterize musical excerpts. The paper also presents the results of new emerging research fields and techniques that investigate the proximity of music genres View full abstract»

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  • Small world distributed access of multimedia data: an indexing system that mimics social acquaintance networks

    Publication Year: 2006 , Page(s): 142 - 153
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1449 KB) |  | HTML iconHTML  

    This paper proposes a technique employing the concept of small-world theory to achieve an acquaintance network made up of various types of media objects. Mirroring the way in which humans keep track of descriptions of their friends and acquaintances, every media object within the Small World Indexing Model (SWIM) actively participates in storing descriptions of the objects that are most similar to itself. This results in an extremely high level of decentralization, where each object participates as an equal member in a peer-to-peer network and no central index is required. Retrieval within this ubiquitously networked environment is performed using an agent-based technology exploiting similarity between query criteria and node-specific descriptions stored locally by each media project. This framework is extremely general in that it can easily be applied to any multimedia data type and also modified to employ any low-level or semantic descriptor View full abstract»

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  • The history of linear prediction

    Publication Year: 2006 , Page(s): 154 - 161
    Cited by:  Papers (5)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (307 KB) |  | HTML iconHTML  

    This paper recollects the events that led to proposing the linear prediction coding (LPC) method, then the multipulse LPC and the code-excited LPC View full abstract»

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Aims & Scope

IEEE Signal Processing Magazine publishes tutorial-style articles on signal processing research and applications, as well as columns and forums on issues of interest.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Min Wu
University of Maryland, College Park
United States 

http://www/ece.umd.edu/~minwu/