Multimedia Database Retrieval

Lieferzeit: Lieferbar innerhalb 14 Tagen

106,99 

Technology and Applications, Multimedia Systems and Applications

ISBN: 3319117815
ISBN 13: 9783319117812
Autor: Muneesawang, Paisarn/Zhang, Ning/Guan, Ling
Verlag: Springer Verlag GmbH
Umfang: xii, 350 S., 31 s/w Illustr., 111 farbige Illustr., 350 p. 142 illus., 111 illus. in color.
Erscheinungsdatum: 03.11.2014
Auflage: 1/2014
Produktform: Gebunden/Hardback
Einband: GEB

Reinforces basic principles for the development of tools and systems in the fieldOffers an application-oriented view of multimedia technology with a balanced perspective on multimedia processingReviews the key recent research in all aspects of multimedia including metadata, image, video, and audioIncludes supplementary material: sn.pub/extras

Artikelnummer: 7158653 Kategorie:

Beschreibung

This book explores multimedia applications that emerged from computer vision and machine learning technologies. These state-of-the-art applications include MPEG-7, interactive multimedia retrieval, multimodal fusion, annotation, and database re-ranking. The application-oriented approach maximizes reader understanding of this complex field. Established researchers explain the latest developments in multimedia database technology and offer a glimpse of future technologies. The authors emphasize the crucial role of innovation, inspiring users to develop new applications in multimedia technologies such as mobile media, large scale image and video databases, news video and film, forensic image databases and gesture databases. With a strong focus on industrial applications along with an overview of research topics, Multimedia Database Retrieval: Technology and Applications is an indispensable guide for computer scientists, engineers and practitioners involved in the development and use of multimedia systems. It also serves as a secondary text or reference for advanced-level students interested in multimedia technologies.

Autorenporträt

InhaltsangabeIntroduction.- Kernel-Based Adaptive Image Retrieval Methods.- Self-Adaptation in Image and Video Retrieval.- Interactive Mobile Visual Search and Recommendation at Internet Scale.- Mobile Landmark Recognition.- Image Retrieval from a Forensic Cartridge Case Database.- Indexing, Object Segmentation, and Event Detection in News and Sports Videos.- Adaptive Retrieval in a P2P Cloud Datacenter.- Scalable Video Genre Classification and Event Detection.- Audio-Visual Fusion for Film Database Retrieval and Classification.- Motion Database Retrieval with Application to Gesture Recognition in a Virtual Realty Dance Training System.

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