
Multimedia Database Retrieval
Technology and Applications
Springer (Publisher)
Published on 10. September 2016
Book
Paperback/Softback
XII, 350 pages
978-3-319-35414-9 (ISBN)
Description
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 ofmultimedia systems. It also serves as a secondary text or reference for advanced-level students interested in multimedia technologies.
More details
Series
Edition
Softcover reprint of the original 1st ed. 2014
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
111 farbige Abbildungen, 31 s/w Abbildungen
XII, 350 p. 142 illus., 111 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 20 mm
Weight
552 gr
ISBN-13
978-3-319-35414-9 (9783319354149)
DOI
10.1007/978-3-319-11782-9
Schweitzer Classification
Other editions
Additional editions

Paisarn Muneesawang | Ning Zhang | Ling Guan
Multimedia Database Retrieval
Technology and Applications
Book
11/2014
Springer
€106.99
Shipment within 10-15 days
Content
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.