{"product_id":"multimedia-information-extraction-isbn-9781118118917","title":"Multimedia Information Extraction","description":"The advent of increasingly large consumer collections of audio (e.g., iTunes), imagery (e.g., Flickr), and video (e.g., YouTube) is driving a need not only for multimedia retrieval but also information extraction from and across media. Furthermore, industrial and government collections fuel requirements for stock media access, media preservation, broadcast news retrieval, identity management, and video surveillance.  While significant advances have been made in language processing for information extraction from unstructured multilingual text and extraction of objects from imagery and video, these advances have been explored in largely independent research communities who have addressed extracting information from single media (e.g., text, imagery, audio).  And yet users need to search for concepts across individual media, author multimedia artifacts, and perform multimedia analysis in many domains.  \u003cp\u003eThis collection is intended to serve several purposes, including reporting the current state of the art, stimulating novel research, and encouraging cross-fertilization of distinct research disciplines. The collection and integration of a common base of intellectual material will provide an invaluable service from which to teach a future generation of cross disciplinary media scientists and engineers. \u003c\/p\u003e \u003cp\u003eForeword ix\u003cbr\u003e \u003ci\u003eAlan F. Smeaton\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003ePreface xiii\u003cbr\u003e \u003ci\u003eMark T. Maybury\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eAcknowledgments xv\u003c\/p\u003e \u003cp\u003eContributors xvii\u003c\/p\u003e \u003cp\u003e1 Introduction 1\u003cbr\u003e \u003ci\u003eMark T. Maybury\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2 Multimedia Information Extraction: History and State of the Art 13\u003cbr\u003e \u003ci\u003eMark T. Maybury\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection 1 Image Extraction 41\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3 Visual Feature Localization for Detecting Unique Objects in Images 45\u003cbr\u003e \u003ci\u003eMadirakshi Das, Alexander C. Loui, and Andrew C. Blose\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4 Entropy-based Analysis of Visual And Geolocation Concepts in Images 63\u003cbr\u003e \u003ci\u003eKeiji Yanai, Hidetoshi Kawakubo, and Kobus Barnard\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5 the Meaning of 3d Shape and Some Techniques To Extract It 81\u003cbr\u003e \u003ci\u003eSven Havemann, Torsten Ullrich, and Dieter W. Fellner\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6 a Data-driven Meaningful Representation Of Emotional Facial Expressions 99\u003cbr\u003e \u003ci\u003eNicolas Stoiber, Gaspard Breton, and Renaud Seguier\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection 2 Video Extraction 113\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7 Visual Semantics for Reducing False Positives in Video Search 119\u003cbr\u003e \u003ci\u003eRohini K. Srihari and Adrian Novischi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8 Automated Analysis of Ideological Bias in Video 129\u003cbr\u003e \u003ci\u003eWei-Hao Lin and Alexander G. Hauptmann\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9 Multimedia Information Extraction in a Live Multilingual News Monitoring System 145\u003cbr\u003e \u003ci\u003eDavid D. Palmer, Marc B. Reichman, and Noah White\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10 Semantic Multimedia Extraction Using Audio and Video 159\u003cbr\u003e \u003ci\u003eEvelyne Tzoukermann, Geetu Ambwani, Amit Bagga, Leslie Chipman, Anthony R. Davis, Ryan Farrell, David Houghton, Oliver Jojic, Jan Neumann, Robert Rubinoff, Bageshree Shevade, and Hongzhong Zhou\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11 Analysis of Multimodal Natural Language Content in Broadcast Video 175\u003cbr\u003e \u003ci\u003ePrem Natarajan, Ehry MacRostie, Rohit Prasad, and Jonathan Watson\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12 Web-based Multimedia Information Extraction Based on Social Redundancy 185\u003cbr\u003e \u003ci\u003eJose San Pedro, Stefan Siersdorfer, Vaiva Kalnikaite, and Steve Whittaker\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13 Information Fusion and Anomaly Detection with Uncalibrated Cameras in Video Surveillance 201\u003cbr\u003e \u003ci\u003eErhan Baki Ermis, Venkatesh Saligrama, and Pierre-Marc Jodoin\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection 3 Audio, Graphics, and Behavior Extraction 217\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e14 Automatic Detection, Indexing, and Retrieval Of Multiple Attributes From Cross-lingual Multimedia Data 221\u003cbr\u003e \u003ci\u003eQian Hu, Fred J. Goodman, Stanley M. Boykin, Randall K. Fish, Warren R. Greiff, Stephen R. Jones, and Stephen R. Moore\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15 Information Graphics in Multimodal Documents 235\u003cbr\u003e \u003ci\u003eSandra Carberry, Stephanie Elzer, Richard Burns, Peng Wu, Daniel Chester, and Seniz Demir\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16 Extracting Information From Human Behavior 253\u003cbr\u003e \u003ci\u003eFabio Pianesi, Bruno Lepri, Nadia Mana, Alessandro Cappelletti, and Massimo Zancanaro\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection 4 Affect Extraction From Audio and Imagery 269\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e17 Retrieval of Paralinguistic Information In Broadcasts 273\u003cbr\u003e \u003ci\u003eBjörn Schuller, Martin Wöllmer, Florian Eyben, and Gerhard Rigoll\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e18 Audience Reactions for Information Extraction About Persuasive Language in Political\u003c\/p\u003e \u003cp\u003eCommunication 289\u003cbr\u003e \u003ci\u003eMarco Guerini, Carlo Strapparava, and Oliviero Stock\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e19 the Need for Affective Metadata in Content-based Recommender Systems for Images 305\u003cbr\u003e \u003ci\u003eMarko TkalČiČ, Jurij TasiČ, and Andrej Košir\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e20 Affect-based Indexing for Multimedia Data 321\u003cbr\u003e \u003ci\u003eGareth J. F. Jones and Ching Hau Chan\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection 5 Multimedia Annotation And Authoring 347\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e21 Multimedia Annotation, Querying, And Analysis in Anvil 351\u003cbr\u003e \u003ci\u003eMichael Kipp\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e22 Toward Formalization of Display Grammar for Interactive Media Production with Multimedia\u003c\/p\u003e \u003cp\u003eInformation Extraction 369\u003cbr\u003e \u003ci\u003eRobin Bargar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e23 Media Authoring with Ontological Reasoning: Use Case for Multimedia Information Extraction 385\u003cbr\u003e \u003ci\u003eInsook Choi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e24 Annotating Significant Relations on Multimedia Web Documents 401\u003cbr\u003e \u003ci\u003eMatusala Addisu, Danilo Avola, Paola Bianchi, Paolo Bottoni, Stefano Levialdi, and Emanuele Panizzi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eAbbreviations and Acronyms 419\u003c\/p\u003e \u003cp\u003eReferences 425\u003c\/p\u003e \u003cp\u003eIndex 461\u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e\u003cb\u003eMARK T. MAYBURY, PhD,\u003c\/b\u003e is an Executive Director at MITRE, a federally funded research and development center. In 2010, Dr. Maybury took a leave of absence from MITRE when appointed to the role of Chief Scientist of the United States Air Force. He is a former member of the board of directors of the Object Management Group and the Air Force Scientific Advisory Board. An IEEE Fellow, Dr. Maybury is a member of the ACM Intelligent User Interface Steering Committee and has served on the Advanced Visual Interfaces Program Committee for over ten years. He holds several patents and has edited, coedited, or coauthored a number of books on information retrieval and related topics.   \u003c\/p\u003e\u003cp\u003e\u003ci\u003e\u003cb\u003eThe definitive guide to the state of the art of multimedia information extraction\u003c\/b\u003e\u003c\/i\u003e \u003c\/p\u003e\u003cp\u003eGovernment analysts, think tank researchers, managers at top websites—basically everyone—is searching for the best ways to access and exploit the vast amounts of multimedia data made available over large networks every day. Written by an international team of experts, \u003ci\u003eMultimedia Information Extraction \u003c\/i\u003eprovides a detailed road map to how that’s done. \u003c\/p\u003e\u003cp\u003eThe first book to address not only multimedia retrieval but also information extraction from and across media, it offers diverse perspectives on how this emerging technology can help meet the growing demand in industry and government for stock media access, media preservation, broadcast news retrieval, identity management, video surveillance, and more. \u003c\/p\u003e\u003cp\u003eIncluding a Foreword by Professor Alan Smeaton, founding coordinator of the international TRECVid, \u003ci\u003eMultimedia Information Extraction\u003c\/i\u003e covers: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eThe fundamental issues in processing and multimedia source extraction\u003c\/li\u003e\n\u003cli\u003eThe history and state of the art of multimedia information extraction\u003c\/li\u003e\n\u003cli\u003eImage and video extraction, with tools ranging from visual feature localization to social redundancy\u003c\/li\u003e\n\u003cli\u003eAffect extraction in audio and imagery, from paralinguistic information retrieval to affect-based indexing\u003c\/li\u003e\n\u003cli\u003eMultimedia annotation and authoring\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003eAn inspiring, much-needed resource for researchers and developers in government, industry, and academia, this book also offers guidance on using the material in the core curriculum of ACM SIGCHI, ACM\/IEEE Computer Science, and ACM\/IEEE Information Technology.\u003c\/p\u003e","brand":"Wiley-IEEE Computer Society Pr","offers":[{"title":"Default Title","offer_id":47989661237477,"sku":"NP9781118118917","price":116.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781118118917.jpg?v=1761785001","url":"https:\/\/k12savings.com\/products\/multimedia-information-extraction-isbn-9781118118917","provider":"K12savings","version":"1.0","type":"link"}