Content-Based Video Retrieval

Name: Content-Based Video Retrieval
Brand: Springer, Berlin
SKU: 9781402076176
Price: 553.26 RON
Availability: InStock

A Database Perspective

Autor: Milan Petkovic, Willem Jonker

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Legare: Copertă tare

Editura: Springer, Berlin

Disponibilitate: În depozitul extern

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Recent advances in computing, communication, and data storage have led to an increasing number of la...

Informații despre carte

Autor

Milan Petkovic, Willem Jonker

Limbă

engleză

Legare

Carte - Copertă tare

Publicat

2003

Pagini

151

EAN

9781402076176

ISBN

1402076177

Enbook ID

01418091

Editura

Springer, Berlin

Greutate

422

Dimensiuni

155 x 235 x 11

Descriere completă

Recent advances in computing, communication, and data storage have led to an increasing number of large digital libraries publicly available on the Internet. In addition to alphanumeric data, other modalities, including video play an important role in these libraries. Ordinary techniques will not retrieve required information from the enormous mass of data stored in digital video libraries. Instead of words, a video retrieval system deals with collections of video records. Therefore, the system is confronted with the problem of video understanding. The system gathers key information from a video in order to allow users to query semantics instead of raw video data or video features. Users expect tools that automatically understand and manipulate the video content in the same structured way as a traditional database manages numeric and textual data. Consequently, content-based search and retrieval of video data becomes a challenging and important problem. This book focuses particularly on content-based video retrieval. After addressing basic concepts and techniques in the field, Content-Based Video Retrieval: A Database Perspective concentrates on the semantic gap problem, i.e., the problem of inferring semantics from raw video data, as the main problem of content-based video retrieval. This book identifies and proposes the integrated use of three different techniques to bridge the semantic gap, namely, spatio-temporal formalization methods, hidden Markov models, and dynamic Bayesian networks. As the problem is approached from a database perspective, the emphasis evolves from a database management system into a video database management system. This system allows a user to retrieve the desired video sequence among voluminous amounts of video data in an efficient and semantically meaningful way. This book also presents a modeling framework and a prototype of a content-based video management system that integrates the three methods and provides efficient, flexible, and scalable content-based video retrieval. The proposed approach is validated in the domain of sport videos for which some experimental results are presented. Content-Based Video Retrieval: A Database Perspective is designed for a professional audience, composed of researchers and practitioners in industry. This book is also suitable as a secondary text for graduate-level students in computer science and electrical engineering.

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Content-Based Video Retrieval

A Database Perspective

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