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Record Nr. |
UNINA9910299843103321 |
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Titolo |
Multimodal Location Estimation of Videos and Images [[electronic resource] /] / edited by Jaeyoung Choi, Gerald Friedland |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
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ISBN |
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Edizione |
[1st ed. 2015.] |
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Descrizione fisica |
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1 online resource (199 p.) |
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Disciplina |
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Soggetti |
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Signal processing |
Image processing |
Speech processing systems |
Electrical engineering |
Multimedia information systems |
Signal, Image and Speech Processing |
Communications Engineering, Networks |
Multimedia Information Systems |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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Introduction -- The Benchmark as a Research Catalyst: Charting the Progress of Geo-Prediction for Social Multimedia -- Large-scale Image Geolocalization -- Vision-based Fine-Grained Location Estimation -- Image-Based Positioning of Mobile Devices in Indoor Environments -- Application of Large-Scale Classification Techniques for Simple Location Estimation Experiments -- Collaborative Multimodal Location Estimation of Consumer Media -- Georeferencing Flickr resources based on multimodal features -- Human vs Machine: Establishing a Human Baseline for Multimodal Location Estimation -- Personalized Travel Navigation and Photo-Shooting Navigation Using Large-Scale Geotags. |
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Sommario/riassunto |
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This book presents an overview of the field of multimodal location estimation, i.e. using acoustic, visual, and/or textual cues to estimate |
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the shown location of a video recording. The authors' sample research results in this field in a unified way integrating research work on this topic that focuses on different modalities, viewpoints, and applications. The book describes fundamental methods of acoustic, visual, textual, social graph, and metadata processing as well as multimodal integration methods used for location estimation. In addition, the text covers benchmark metrics and explores the limits of the technology based on a human baseline. · Discusses localization of multimedia data; · Examines fundamental methods of establishing location metadata for images and videos (other than GPS tagging); · Covers Data-Driven as well as Semantic Location Estimation. |
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