Multimedia Database Retrieval: Technology and Applications by Paisarn MuneesawangMultimedia Database Retrieval: Technology and Applications by Paisarn Muneesawang

Multimedia Database Retrieval: Technology and Applications

byPaisarn Muneesawang, Ning Zhang, Ling Guan

Hardcover | November 3, 2014

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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.
Title:Multimedia Database Retrieval: Technology and ApplicationsFormat:HardcoverDimensions:350 pagesPublished:November 3, 2014Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3319117815

ISBN - 13:9783319117812

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Table of Contents

Introduction.- 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.